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jarvis-at-skic e22d3a5c13 docs: separate workflow effectiveness from skill health
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2026-10-08 11:05:00 +00:00
jarvis-at-skic 386133c8b6 Merge pull request 'docs: separate Measurement registry and workflow Baseline' (#35) from feat/measurement-baseline-separation into main
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2026-10-07 06:47:31 -07:00
jarvis-at-skic abe00994a1 docs: [verified] separate Measurement registry and workflow Baseline
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2026-10-07 13:33:07 +00:00
jarvis-at-skic c4b4c38e62 Merge pull request 'docs: separate metric pages under Measurement' (#34) from feat/measurement-metric-pages into main
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2026-10-06 16:26:44 -07:00
jarvis-at-skic 85852f0744 docs: [verified] move metric contracts under Measurement
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2026-10-06 23:25:30 +00:00
jarvis-at-skic b9c2047c61 Merge pull request 'feat: art-direct five Skills Adoption stories' (#33) from feat/skills-topic-compositions into main
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2026-10-06 15:37:16 -07:00
jarvis-at-skic a35cade49c feat: [verified] compose Skills Adoption diagrams around their stories
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2026-10-06 22:35:48 +00:00
jarvis-at-skic ef169cec58 Merge pull request 'fix: expose every documentation page in navigation' (#32) from fix/all-docs-sidebar into main
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2026-10-06 13:15:15 -07:00
jarvis-at-skic e0afa78eb2 test: [verified] include Reference in measurement navigation
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2026-10-06 20:14:19 +00:00
jarvis-at-skic e087adab1e fix: [verified] expose all documentation in reachable sidebars
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2026-10-06 20:00:08 +00:00
jarvis-at-skic 325363d89c Merge pull request 'feat: wider, richer Skills Adoption diagrams' (#31) from feat/skills-adoption-stories into main
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2026-10-06 12:41:28 -07:00
jarvis-at-skic ad7312b65a feat: [verified] widen Skills Adoption diagram stories
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2026-10-06 19:37:49 +00:00
jarvis-at-skic 3238e1d809 Merge pull request 'docs: group Strategy into Skills Adoption and Autonomous Agent stages' (#30) from feat/strategy-stage-navigation into main
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2026-10-06 12:07:57 -07:00
jarvis-at-skic fe4c3509d1 docs: [verified] group Strategy into adoption and autonomy stages
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2026-10-06 19:07:00 +00:00
jarvis-at-skic 8a7dbea852 Merge pull request 'docs: connect skills-first Roadmap to autonomous Target' (#29) from feat/roadmap-skills-to-target into main
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2026-10-06 04:36:20 -07:00
jarvis-at-skic e10b03dff4 docs: [verified] connect skills-first Roadmap to autonomous Target
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2026-10-06 11:34:39 +00:00
jarvis-at-skic 733d6f2ece Merge pull request 'fix: replace Roadmap with minimal adoption timeline' (#28) from fix/roadmap-minimal-timeline into main
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2026-10-06 00:35:15 -07:00
jarvis-at-skic 2a4e058684 fix: [verified] simplify Roadmap adoption timeline
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2026-10-06 07:25:53 +00:00
jarvis-at-skic 63f38597a6 Merge pull request 'fix: separate Target lifecycle channels and standalone typography' (#27) from fix/standalone-svg-typography into main
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2026-10-05 14:13:27 -07:00
jarvis-at-skic 0248baa97b fix: [verified] separate Target lifecycle channels and export typography
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2026-10-05 21:11:29 +00:00
jarvis-at-skic 7e3696d2d7 Merge pull request 'fix: share Target central-agent edge midpoints' (#26) from fix/target-midpoint-connectors into main
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2026-10-05 13:14:33 -07:00
jarvis-at-skic 15c5dcb31d fix: align Target governance links to shared edge midpoints
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2026-10-05 20:12:20 +00:00
jarvis-at-skic 64b2d6dae8 Merge pull request 'docs: rename Target contributors to AI Agent' (#25) from docs/target-ai-agent into main
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2026-10-05 12:54:21 -07:00
jarvis-at-skic 20e6f4899c docs: rename Target contributors to AI Agent
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2026-10-05 19:51:04 +00:00
jarvis-at-skic 2f68e60cec Merge pull request 'docs: redesign Roadmap as a native five-stage workflow' (#24) from docs/roadmap-workflow into main
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2026-10-05 12:36:42 -07:00
jarvis-at-skic e149131307 docs: redesign Roadmap as a native five-stage workflow
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2026-10-05 19:35:14 +00:00
jarvis-at-skic 2d63313180 Merge pull request 'docs: start Roadmap with code-quality and process assessment' (#23) from docs/assessment-first-roadmap into main
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2026-10-05 11:51:54 -07:00
jarvis-at-skic 1de7d16d09 docs: start roadmap with code and process assessment
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2026-10-05 18:50:28 +00:00
jarvis-at-skic b679e6b2b5 Merge pull request 'docs: make Skills Measurement an adoption collection plan' (#22) from docs/skills-measurement-plan into main
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2026-10-05 11:36:20 -07:00
jarvis-at-skic 8dd54f0ab6 docs: explain skills adoption measurement and collection
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2026-10-05 18:33:40 +00:00
jarvis-at-skic 8bfcb3f81d Merge pull request 'fix: canonical Target navigation and Roadmap second' (#21) from fix/strategy-navigation into main
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2026-10-05 11:19:15 -07:00
jarvis-at-skic baf79e125b fix: make Target canonical and place Roadmap second
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2026-10-05 18:16:57 +00:00
jarvis-at-skic 9651417ba7 Merge pull request 'docs: label central autonomous agent Human Controlled' (#20) from docs/target-human-controlled into main
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2026-10-05 11:02:33 -07:00
jarvis-at-skic 4cc2bb4dfd docs: label central autonomous agent Human Controlled
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2026-10-05 17:59:59 +00:00
jarvis-at-skic afb6a97e97 Merge pull request 'docs: center Target lifecycle on autonomous agent' (#19) from docs/target-central-agent into main
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2026-10-05 10:25:47 -07:00
jarvis-at-skic 1057433c2a docs: center Target lifecycle on autonomous agent
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2026-10-05 17:23:56 +00:00
jarvis-at-skic 504d9f8845 Merge pull request 'docs: lead Strategy with autonomous SDLC cycle' (#18) from docs/autonomous-sdlc-cycle into main
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2026-10-05 09:34:42 -07:00
jarvis-at-skic 29beebb379 docs: lead Strategy with autonomous SDLC cycle
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2026-10-05 16:32:51 +00:00
jarvis-at-skic e95b85afee Merge pull request 'fix: right-align inline diagram controls' (#17) from fix/right-align-inline-controls into main
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2026-10-05 05:51:58 -07:00
96 changed files with 6083 additions and 1983 deletions

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{"id":"ui-ux","type":"backend","label":"UI/UX","sublabel":"03","pos":[100,880],"size":[240,100]},
{"id":"planning","type":"backend","label":"Planning","sublabel":"04","pos":[100,1100],"size":[240,100]},
{"id":"delivery","type":"backend","label":"Delivery","sublabel":"05","pos":[100,1320],"size":[240,100]},
{"id":"uat","type":"backend","label":"UAT","sublabel":"06","pos":[100,1540],"size":[240,100]},
{"id":"security","type":"backend","label":"Security","sublabel":"07","pos":[100,1760],"size":[240,100]},
{"id":"releases","type":"backend","label":"Releases","sublabel":"08","pos":[100,1980],"size":[240,100]},
{"id":"code-scope","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[400,440],"size":[240,100]},
{"id":"code-architecture","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[400,660],"size":[240,100]},
{"id":"code-ui-ux","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[400,880],"size":[240,100]},
{"id":"code-planning","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[400,1100],"size":[240,100]},
{"id":"code-delivery","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[400,1320],"size":[240,100]},
{"id":"code-uat","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[400,1540],"size":[240,100]},
{"id":"code-security","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[400,1760],"size":[240,100]},
{"id":"code-releases","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[400,1980],"size":[240,100]}
],
"connections": [
{
"id": "flow-0",
"from": "people",
"to": "coordinator",
"label": "Authorize scope"
},
{
"id": "flow-1",
"from": "coordinator",
"to": "clients",
"label": "Route tasks"
},
{
"id": "flow-2",
"from": "registry",
"to": "coordinator",
"label": "Guide"
},
{
"id": "flow-3",
"from": "registry",
"to": "clients",
"label": "Guide"
},
{
"id": "flow-4",
"from": "clients",
"to": "gates",
"label": "Propose"
},
{
"id": "flow-5",
"from": "gates",
"to": "approval",
"label": "Evidence"
},
{
"id": "flow-6",
"from": "approval",
"to": "release",
"label": "Authorize"
}
{"id":"govern-scope","from":"agent","to":"scope","label":"","variant":"security","fromSide":"left","toSide":"left","via":[[60,260],[60,490]]},
{"id":"govern-architecture","from":"agent","to":"architecture","label":"","variant":"security","fromSide":"left","toSide":"left","via":[[60,260],[60,710]]},
{"id":"govern-ui-ux","from":"agent","to":"ui-ux","label":"","variant":"security","fromSide":"left","toSide":"left","via":[[60,260],[60,930]]},
{"id":"govern-planning","from":"agent","to":"planning","label":"","variant":"security","fromSide":"left","toSide":"left","via":[[60,260],[60,1150]]},
{"id":"govern-delivery","from":"agent","to":"delivery","label":"","variant":"security","fromSide":"left","toSide":"left","via":[[60,260],[60,1370]]},
{"id":"govern-uat","from":"agent","to":"uat","label":"","variant":"security","fromSide":"left","toSide":"left","via":[[60,260],[60,1590]]},
{"id":"govern-security","from":"agent","to":"security","label":"","variant":"security","fromSide":"left","toSide":"left","via":[[60,260],[60,1810]]},
{"id":"govern-releases","from":"agent","to":"releases","label":"","variant":"security","fromSide":"left","toSide":"left","via":[[60,260],[60,2030]]},
{"id":"stage-1","from":"scope","to":"architecture","label":"Then","variant":"emphasis","fromSide":"bottom","toSide":"top"},
{"id":"stage-2","from":"architecture","to":"ui-ux","label":"Then","variant":"emphasis","fromSide":"bottom","toSide":"top"},
{"id":"stage-3","from":"ui-ux","to":"planning","label":"Then","variant":"emphasis","fromSide":"bottom","toSide":"top"},
{"id":"stage-4","from":"planning","to":"delivery","label":"Then","variant":"emphasis","fromSide":"bottom","toSide":"top"},
{"id":"stage-5","from":"delivery","to":"uat","label":"Then","variant":"emphasis","fromSide":"bottom","toSide":"top"},
{"id":"stage-6","from":"uat","to":"security","label":"Then","variant":"emphasis","fromSide":"bottom","toSide":"top"},
{"id":"stage-7","from":"security","to":"releases","label":"Then","variant":"emphasis","fromSide":"bottom","toSide":"top"},
{"id":"stage-8","from":"releases","to":"scope","label":"Repeat indefinitely","variant":"emphasis","fromSide":"bottom","toSide":"top","via":[[220,2140],[680,2140],[680,380],[220,380]],"labelAt":[440,2180]},
{"id":"contribute-scope","from":"code-scope","to":"scope","label":"Contribute","variant":"dashed","fromSide":"left","toSide":"right"},
{"id":"contribute-architecture","from":"code-architecture","to":"architecture","label":"Contribute","variant":"dashed","fromSide":"left","toSide":"right"},
{"id":"contribute-ui-ux","from":"code-ui-ux","to":"ui-ux","label":"Contribute","variant":"dashed","fromSide":"left","toSide":"right"},
{"id":"contribute-planning","from":"code-planning","to":"planning","label":"Contribute","variant":"dashed","fromSide":"left","toSide":"right"},
{"id":"contribute-delivery","from":"code-delivery","to":"delivery","label":"Contribute","variant":"dashed","fromSide":"left","toSide":"right"},
{"id":"contribute-uat","from":"code-uat","to":"uat","label":"Contribute","variant":"dashed","fromSide":"left","toSide":"right"},
{"id":"contribute-security","from":"code-security","to":"security","label":"Contribute","variant":"dashed","fromSide":"left","toSide":"right"},
{"id":"contribute-releases","from":"code-releases","to":"releases","label":"Contribute","variant":"dashed","fromSide":"left","toSide":"right"}
]
}
+43 -148
View File
@@ -1,156 +1,51 @@
{
"schema_version": 1,
"diagram_type": "architecture",
"meta": {
"title": "TO-BE: coordination without authority transfer",
"output": "static/diagrams/strategy-target/index.html",
"quality_profile": "showcase",
"legend": {
"mode": "hidden"
}
},
"meta": {"title": "TO-BE: autonomous SDLC, human direction", "output": "static/diagrams/strategy-target/index.html", "quality_profile": "showcase", "legend": {"mode": "hidden"}},
"components": [
{
"id": "people",
"type": "backend",
"label": "People authorize",
"sublabel": "Retain accountability",
"pos": [
20,
20
],
"size": [
180,
60
]
},
{
"id": "coordinator",
"type": "backend",
"label": "SDLC coordinator",
"sublabel": "Routes approved work",
"pos": [
20,
140
],
"size": [
180,
60
]
},
{
"id": "clients",
"type": "backend",
"label": "Local coding agents",
"sublabel": "Propose changes",
"pos": [
20,
260
],
"size": [
180,
60
]
},
{
"id": "gates",
"type": "security",
"label": "Repository + CI",
"sublabel": "Verify exact revision",
"pos": [
20,
380
],
"size": [
180,
60
]
},
{
"id": "registry",
"type": "backend",
"label": "Governed skills",
"sublabel": "Pinned + qualified",
"pos": [
260,
140
],
"size": [
180,
60
]
},
{
"id": "approval",
"type": "security",
"label": "Human approval",
"sublabel": "Exact artifact + scope",
"pos": [
260,
380
],
"size": [
180,
60
]
},
{
"id": "release",
"type": "security",
"label": "Release service",
"sublabel": "Production credentials",
"pos": [
260,
500
],
"size": [
180,
60
]
}
{"id":"agent","type":"security","label":"Autonomous agent","sublabel":"Human Controlled","pos":[465,450],"size":[270,90]},
{"id":"scope","type":"backend","label":"Scope","sublabel":"01","pos":[510,187.5],"size":[180,75]},
{"id":"architecture","type":"backend","label":"Architecture","sublabel":"02","pos":[780,187.5],"size":[180,75]},
{"id":"ui-ux","type":"backend","label":"UI/UX","sublabel":"03","pos":[780,457.5],"size":[180,75]},
{"id":"planning","type":"backend","label":"Planning","sublabel":"04","pos":[780,727.5],"size":[180,75]},
{"id":"delivery","type":"backend","label":"Delivery","sublabel":"05","pos":[510,727.5],"size":[180,75]},
{"id":"uat","type":"backend","label":"UAT","sublabel":"06","pos":[240,727.5],"size":[180,75]},
{"id":"security","type":"backend","label":"Security","sublabel":"07","pos":[240,457.5],"size":[180,75]},
{"id":"releases","type":"backend","label":"Releases","sublabel":"08","pos":[240,187.5],"size":[180,75]},
{"id":"code-scope","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[510,37.5],"size":[180,75]},
{"id":"code-architecture","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[780,37.5],"size":[180,75]},
{"id":"code-ui-ux","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[1005,457.5],"size":[180,75]},
{"id":"code-planning","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[780,877.5],"size":[180,75]},
{"id":"code-delivery","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[510,877.5],"size":[180,75]},
{"id":"code-uat","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[240,877.5],"size":[180,75]},
{"id":"code-security","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[15,457.5],"size":[180,75]},
{"id":"code-releases","type":"frontend","label":"AI Agent","sublabel":"Human-controlled","pos":[240,37.5],"size":[180,75]}
],
"connections": [
{
"id": "flow-0",
"from": "people",
"to": "coordinator",
"label": "Authorize scope"
},
{
"id": "flow-1",
"from": "coordinator",
"to": "clients",
"label": "Route tasks"
},
{
"id": "flow-2",
"from": "registry",
"to": "coordinator",
"label": "Guide"
},
{
"id": "flow-3",
"from": "registry",
"to": "clients",
"label": "Guide"
},
{
"id": "flow-4",
"from": "clients",
"to": "gates",
"label": "Propose"
},
{
"id": "flow-5",
"from": "gates",
"to": "approval",
"label": "Evidence"
},
{
"id": "flow-6",
"from": "approval",
"to": "release",
"label": "Authorize"
}
{"id":"govern-scope","from":"agent","to":"scope","label":"","variant":"security","fromSide":"top","toSide":"bottom","route":"straight"},
{"id":"govern-architecture","from":"agent","to":"architecture","label":"","variant":"security","fromSide":"top","toSide":"bottom","via":[[600,345],[870,345]]},
{"id":"govern-ui-ux","from":"agent","to":"ui-ux","label":"","variant":"security","fromSide":"right","toSide":"left","route":"straight"},
{"id":"govern-planning","from":"agent","to":"planning","label":"","variant":"security","fromSide":"bottom","toSide":"top","via":[[600,645],[870,645]]},
{"id":"govern-delivery","from":"agent","to":"delivery","label":"","variant":"security","fromSide":"bottom","toSide":"top","route":"straight"},
{"id":"govern-uat","from":"agent","to":"uat","label":"","variant":"security","fromSide":"bottom","toSide":"top","via":[[600,645],[330,645]]},
{"id":"govern-security","from":"agent","to":"security","label":"","variant":"security","fromSide":"left","toSide":"right","route":"straight"},
{"id":"govern-releases","from":"agent","to":"releases","label":"","variant":"security","fromSide":"top","toSide":"bottom","via":[[600,345],[330,345]]},
{"id":"stage-1","from":"scope","to":"architecture","label":"Then","variant":"emphasis","fromSide":"right","toSide":"left"},
{"id":"stage-2","from":"architecture","to":"ui-ux","label":"Then","variant":"emphasis","fromSide":"bottom","toSide":"top"},
{"id":"stage-3","from":"ui-ux","to":"planning","label":"Then","variant":"emphasis","fromSide":"bottom","toSide":"top"},
{"id":"stage-4","from":"planning","to":"delivery","label":"Then","variant":"emphasis","fromSide":"left","toSide":"right"},
{"id":"stage-5","from":"delivery","to":"uat","label":"Then","variant":"emphasis","fromSide":"left","toSide":"right"},
{"id":"stage-6","from":"uat","to":"security","label":"Then","variant":"emphasis","fromSide":"top","toSide":"bottom"},
{"id":"stage-7","from":"security","to":"releases","label":"Then","variant":"emphasis","fromSide":"top","toSide":"bottom"},
{"id":"stage-8","from":"releases","to":"scope","label":"Repeat indefinitely","variant":"emphasis","fromSide":"right","toSide":"left","labelAt":[465,170]},
{"id":"contribute-scope","from":"code-scope","to":"scope","label":"Contribute","variant":"dashed","fromSide":"bottom","toSide":"top"},
{"id":"contribute-architecture","from":"code-architecture","to":"architecture","label":"Contribute","variant":"dashed","fromSide":"bottom","toSide":"top"},
{"id":"contribute-ui-ux","from":"code-ui-ux","to":"ui-ux","label":"Contribute","variant":"dashed","fromSide":"left","toSide":"right","labelAt":[990,570]},
{"id":"contribute-planning","from":"code-planning","to":"planning","label":"Contribute","variant":"dashed","fromSide":"top","toSide":"bottom"},
{"id":"contribute-delivery","from":"code-delivery","to":"delivery","label":"Contribute","variant":"dashed","fromSide":"top","toSide":"bottom"},
{"id":"contribute-uat","from":"code-uat","to":"uat","label":"Contribute","variant":"dashed","fromSide":"top","toSide":"bottom"},
{"id":"contribute-security","from":"code-security","to":"security","label":"Contribute","variant":"dashed","fromSide":"right","toSide":"left","labelAt":[220,570]},
{"id":"contribute-releases","from":"code-releases","to":"releases","label":"Contribute","variant":"dashed","fromSide":"bottom","toSide":"top"}
]
}
+3 -1
View File
@@ -15,7 +15,7 @@ description: Author typed JSON diagrams and embed their local interactive viewer
| Dataflow | Sources, processing and destinations |
| Lifecycle | States and transitions |
The standalone viewer provides pan/zoom, node inspection, search/focus, relationship tracing, light/dark themes, and an export menu. Motion is opt-in. The Organization views exercise architecture mode; other diagram types use the same build interface but do not yet have portal-specific examples. Browser-dependent exports such as video are not acceptance-tested by this integration.
The standalone viewer provides pan/zoom, node inspection, search/focus, relationship tracing, light/dark themes, and an export menu. Motion is opt-in. The Organization views exercise architecture mode; Roadmap uses native Workflow v2 with a horizontal desktop path and the same stages stacked on mobile. Other diagram types use the same build interface but do not yet have portal-specific examples. Browser-dependent exports such as video are not acceptance-tested by this integration.
## Author a diagram
@@ -23,6 +23,8 @@ Create `diagrams/<name>.<type>.json` using the matching schema and authoring gui
Set `meta.output` to `static/diagrams/<name>/index.html`. The build validates the typed source with the upstream showcase profile, renders locally, checks the artifact, and publishes the standalone HTML. Editable JSON stays in the repository; the portal does not publish source-download files.
Roadmap has a scoped multiline typography adapter in `scripts/roadmap-viewer.mjs`. Its two `.workflow.json` sources use the native v2 schema, one lane, `mainPath`, logical columns and native routes. The native renderer validates the schema and solves geometry; the adapter wraps the existing action/output/exit copy, removes the redundant lane frame and trims empty canvas. The final artifact then passes the upstream showcase composition checker. This path records source, adapter and final artifact hashes in private `.cache/archify/*.portal.json` receipts, not upstream `deliver` provenance. Keep the vendor unchanged and run the Roadmap browser check at 1440, 390 and 320 pixels after any copy or sizing change. Typography is embedded in the SVG so exports retain it.
```sh
pnpm diagrams:build
pnpm test
+4 -1
View File
@@ -28,7 +28,10 @@ Include `title` and `description` frontmatter. Place each page in its owning sec
| Contribution | `docs/contribution/` | `sidebars/contribution.ts` |
| Portal maintenance and reference | `docs/core/` | `sidebars.ts` |
Keep these content roots disjoint. Preserve existing URLs when moving pages. Specific AI initiatives and organizational reporting lines remain subject to agreement.
Keep these content roots disjoint. Preserve existing URLs unless a URL migration is explicitly approved; provide precise redirects for approved moves. Metric details live on individual canonical pages directly under Measurement, alongside shared collection safeguards and the synthetic example. Specific AI initiatives and organizational reporting lines remain subject to agreement.
Every published documentation page must have a navigable sidebar entry. Nested references are welcome; hidden documentation is not. Linked category overviews count as entries, but an in-page anchor is not a separate document. Portal-maintenance pages keep their existing `/docs/` routes and dedicated sidebar, reachable from Contribution → Portal maintenance.
`pnpm verify:build` compares all Docusaurus-generated document IDs/routes with resolved sidebar trees (including linked category overviews), checks reachability from the navbar, rejects missing/duplicate entries and unclassified HTML routes, and checks every document’s local links and anchors. The inventory is written to `.cache/sidebar-coverage.json`. Only the homepage, not-found page, search-results UI, legacy Strategy redirect, exact legacy measurement-contracts hash-aware redirect and standalone diagram viewers are non-document HTML routes; no documentation page is exempt. The metric migration manifest in `research/ai-adoption/measurement-migration.json` records old anchors, canonical IDs/URLs, implementation status and preserved-contract hashes.
## Validate the change
+58
View File
@@ -0,0 +1,58 @@
---
id: baseline
title: Baseline
sidebar_label: Baseline
description: Understand a workflow, select relevant candidate metrics and establish feasible starting evidence for later comparison.
pagination_prev: measurement/index
pagination_next: skills-governance
hide_table_of_contents: true
---
import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
<div className="strategy-content">
Establish a starting position for one workflow as adoption reaches it. This is not a mandatory company-wide baseline of every metric in the [Measurement registry](./measurement/index.mdx).
<ArchifyDiagram name="strategy-baseline" title="From current workflow through relevant selection and feasible evidence to a starting position and later comparison" story />
**Target operating model — no actual baseline values or approved thresholds are established here.** Missing evidence remains an explicit gap, not an invented starting value.
## Understand the current workflow
Describe the task, team or service, intended outcome, current tools, handoffs, controls and known friction. Bound what is in and out of scope. For Delivery, start with codebase structure and existing principles, system-logic sources, tests, builds and packaging, then deployments. Record current practice, including any existing AI use; do not label it “no-skill” unless that is true.
## Select relevant metrics, with reasons
Start with **Workflow effectiveness**: select relevant current-workflow outcomes before standardized skills adoption—accepted work, delivery time, failures/rework, cost, human effort/experience or business acceptance where the contracts apply. Choose the registry entries that answer this workflow's questions. Record why each selected metric applies, what decision it can inform, and why other candidates are irrelevant or deferred. There is no required universal subset. A service-level DORA metric, a qualification test and a people survey have different populations; they are not interchangeable.
Keep **Skills effectiveness & health** separate. If no applicable skills exist, selection, bundle, adoption and review measures may be N/A, not zero; they are not prerequisites for baselining current work. If skills already exist, record that starting context and qualify named revisions separately. Do not mix sandbox skill evaluations into validated workflow task success or live policy-effect rates.
Agree what counts as a started task, independent acceptance and completed follow-up before counting outcomes. Freeze eligibility and acceptance rules and verify event joins. Select a complete comparable workflow cycle and a predeclared precision/sample requirement appropriate to the decision. Do not select a convenient end date after seeing results. Where those requirements cannot be met, record the resulting evidence limitation.
## Agree feasible evidence
Confirm collection feasibility, period, sources, owner, independent reviewer, access, lawful basis, privacy and retention before collecting. Use the [shared safeguards](./measurement/collection-and-safeguards.mdx) and each selected contract's input requirements. Proposed owner/cadence entries are not already assigned responsibilities.
Start with a controlled worksheet or export if automation is unavailable. Join task IDs to acceptance records, PR/commit IDs, CI results and later defects where relevant; test source coverage and permissions. Repository and CI evidence support verification, but a green build alone is not task acceptance. Record exact skill revisions and client/model configurations when present; keep missing versions unknown.
## Record the starting position
Collect prospective current-practice evidence over the agreed period. Record actual starting values only when supported by traceable evidence. Include units, population, observation period, counts, exclusions, source coverage, calculation version, uncertainty and limitations. Zero denominators mean “not available,” not zero performance.
For each selected metric, keep one of these explicit records:
- **Available:** evidenced starting value, source links, calculation, owner and limits.
- **Unavailable:** missing input or permission, affected comparison, responsible owner and proposed next action or review point. Never fill the gap with the synthetic example or an assumed industry value.
Record deferred and non-applicable candidates separately from selected-but-unavailable metrics. This page is the recording method, not an Eldorado baseline report or a set of approved targets.
## Keep later evaluation comparable
Retain task class, service, skill, client/model configuration and concurrent changes. In [Adoption](./skills-adoption.mdx), use the same agreed eligibility, acceptance and observation rules; in [Maintenance](./skills-maintenance.mdx), record any changes and breaks in comparability rather than silently replacing the starting position.
A matched or randomized comparison may be used when practical and ethical. Label observational trends as descriptive, not causal ROI; report confounding, selection and uncertainty. Missing or small samples limit conclusions. Baseline values describe current practice; they do not establish acceptable risk or authorize expansion.
**Next:** [Govern skill ownership and authority →](./skills-governance.mdx)
</div>
-54
View File
@@ -1,54 +0,0 @@
---
id: index
title: AI adoption strategy
description: Govern skills first; outcomes before activity; explicit target status.
slug: /
hide_table_of_contents: true
---
import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
<div className="strategy-content">
**TO-BE · Target operating model — not installed controls or company results.**
## How do we reach dependable AI-assisted work?
Start with governed skills, then widen coordination only when evidence supports it. The destination is one logical SDLC coordinator alongside people using qualified local coding agents.
<ArchifyDiagram name="strategy-journey" title="Skills and quality evidence precede wider coordination" story />
- **Skills first:** reusable working knowledge, not permission to act.
- **People stay accountable:** the six departments and eleven teams keep their decisions.
- **Outcomes before activity:** quality, risk and total cost determine whether to continue.
<details>
<summary>Strategy rationale and reading map</summary>
**TO-BE · Target operating model.** Introduction depends on the [roadmap gates](./roadmap.mdx); these pages do not describe installed controls or measured company results.
### Govern skills first, expand authority only with evidence
Eldorado's target is to make AI-assisted work dependable across the organization: useful guidance, clear human ownership, controlled execution and measurable outcomes. The first investment is a governed skills system, not an autonomous replacement for the organization. A skill packages reusable working knowledge, prerequisites and verification steps. It helps an agent perform a task; it does not grant permission or guarantee that the work is correct.
The target combines one logical SDLC coordinating agent with developer choice on local laptops. Copilot, Claude Code and Cline remain client options within a qualified support matrix. They receive the same reviewed portable skill content through client-specific adapters. Repository, CI and release services remain the enforcement points, independently of what any agent says or which local tool produced a change.
The strategy describes the intended operating model and the evidence required to introduce it. It does not establish that these controls are installed, that every client is supported, or that AI has improved Eldorado's performance. The current reference is the documented six-department organization. Rollout begins by validating actual clients, responsibilities, data boundaries and available evidence.
Success means accepted outcomes with maintained quality, controlled risk and understood total cost. Faster activity without reliable outcomes is not success. More skill invocations, generated lines or tool subscriptions are not productivity targets. People remain accountable for product, customer, financial and personnel decisions.
## Navigate the strategy
- [Target operating model](./target-operating-model.mdx) — One logical coordinator; local client choice; independent authority; all departments.
- [Skills governance](./skills-governance.mdx) — Contract, lifecycle, decision rights, adapters, locking, exceptions.
- [Skills quality](./skills-quality.mdx) — Risk tiers, independent evaluation, repeated trials, adversarial conformance.
- [Skills adoption](./skills-adoption.mdx) — Workflow-led coaching, client choice, feedback, manual path.
- [Measurement](./measurement.mdx) — Full KPI contracts, minimal events, illustrative calculations, privacy and limits.
- [Skills maintenance](./skills-maintenance.mdx) — Review, drift, deprecation, rollback and incident handling.
- [Roadmap](./roadmap.mdx) — Evidence-gated phases, no promised dates or budgets.
</details>
**Next:** [See how people, skills and delivery controls connect →](./target-operating-model.mdx)
</div>
-385
View File
@@ -1,385 +0,0 @@
---
id: measurement
title: Measurement
description: Full KPI contracts, minimal events, illustrative calculations, privacy and limits.
hide_table_of_contents: true
---
import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
<div className="strategy-content">
**TO-BE · Target operating model — not installed controls or company results.**
## Is AI-assisted work worth continuing?
Judge accepted outcomes alongside quality, delivery flow, risk, cost and human experience. Validate source coverage before calculating; missing evidence is unknown, not success.
<ArchifyDiagram name="strategy-measurement" title="Collect evidence, validate it, calculate balanced measures and decide" story />
**Illustrative only:** 1 accepted task ÷ 4 matured starts × 100 = **25%** confirmed success. One unresolved task stays in the denominator; known-outcome coverage is **75%**. These are synthetic data, not Eldorado results.
- **16 contracts:** exact definitions below; 9 prototype calculations, 7 explicitly unimplemented metrics.
- **Balanced evidence:** no productivity rankings, composite score or causal ROI claim.
- **Privacy first:** no raw prompts or code by default; protect small cohorts and agree retention before collection.
<details>
<summary>Collection, baseline, event and privacy contracts</summary>
**TO-BE · Target operating model.** Introduction depends on the [roadmap gates](./roadmap.mdx); these pages do not describe installed controls or measured company results.
### Decide what counts before counting
Use the metric contracts below for exact definitions. Every report states its eligible population, observation window, numerator and denominator or distribution sample count, source coverage, exclusions and calculation version. Zero denominators return “not available.” Missing telemetry is unknown, not inactivity, compliance or success. Examples are explicitly synthetic and illustrative.
Begin with task acceptance, repository, CI, deployment and incident systems because they can independently establish outcomes. Add catalog/version inventory and task-level declarations. Client telemetry is supplementary and version-dependent; enabling rich tool details may collect sensitive commands and identifiers. Do not enable it merely to count skills. A normalized adapter may report approved skill identifiers without forwarding raw arguments.
Validated success uses all eligible initiated tasks whose predeclared observation window has matured. Failed and abandoned tasks remain nonsuccess. Unresolved or unobserved outcomes remain in the denominator, with known-outcome coverage shown alongside the conservative confirmed-success share. They are not relabeled as observed failure. A task cancelled before start is excluded; cancellation after start remains visible. Count a task once across retries and multiple skills. For timeliness, also show unfinished work and age; accepted-only lead-time distributions have survivorship limitations.
Track all five service-level DORA measures: commit-to-production lead time, deployment frequency, change fail rate, failed deployment recovery time and deployment rework rate. Do not substitute PR-open-to-merge time or all-incident MTTR. Pair them with matured escaped-quality rates, policy effects, total cost per accepted outcome, support coverage, adoption, human experience and catalog maintenance. Keep customer/business outcomes linked to their departmental hypotheses; do not infer conversion, trust or revenue improvement from delivery telemetry.
### Baseline and interpretation
Before a pilot, freeze eligibility and acceptance rules and verify event joins. Collect prospective no-skill/current-practice evidence over a complete comparable workflow cycle and until the preregistered precision/sample requirement is met. Do not select a convenient end date after seeing results. Retain task class, service, skill, client/model configuration and concurrent changes. A matched or randomized comparison may be used when practical and ethical; label observational trends as descriptive and report confounding, selection and uncertainty.
Elapsed time and human effort are different quantities. Parallel agents may reduce waiting while increasing review or compute. Include failed attempts and human review/rework in cost, do not multiply a multi-skill task's value across every invocation, and do not convert survey perceptions into proven time savings. Small or incomplete populations yield evidence limits, not an ROI percentage.
### Event and privacy contract
Use a versioned event envelope and required fields per event. Source producer plus event ID deduplicates transport retries. Conflicting payloads under the same key are quarantined. Attempts have distinct IDs under one task. Domain IDs deduplicate deployments, defects and approvals even when multiple feeds describe them. Late arrivals produce versioned aggregate corrections; never silently overwrite a published result. Preserve occurrence and receipt times, reject impossible orderings and flag clock skew. Missing terminal events remain unresolved until the work owner reconciles them.
Many-to-many task/attempt/skill/client associations preserve exact immutable versions. Unknown version stays null with a reason; never assign the latest revision retroactively. Client declarations, server facts and self-reports remain separately labeled. A skill-loaded event is evidence of loading only. The minimal prototype can operate without actor identity except where a lawful, necessary adoption denominator requires pseudonymous cohort membership.
The privacy starting proposal is 30 days for raw structured analytics events and 12 months for aggregated trends, subject to the responsible owners' review. Keep the approved catalog/approval record for the supported revision's lifetime and its required audit period, which must be decided separately. Incident evidence uses a restricted, explicitly authorized hold and deletion schedule, not an indefinite analytics exception. Suppress reports below five people and prohibit drill-down or overlapping cohort slices that reconstruct identities. Five is a proposed minimum, not a guarantee against re-identification. No raw prompts, code, screens, customer cases or secrets are collected by default. Publish the purpose, lawful collection basis, access/deletion route and retention before collecting. Consent is not presumed to be an appropriate employment-law basis.
</details>
<details>
<summary>All 16 KPI contracts — formulas, populations, owners and limits</summary>
## Metric contracts
Each contract is a prospective collection design. No live source or observed baseline is established. N and D refer to the numerator and denominator shown for that metric.
### Validated task success
Confirmed independently accepted tasks as a share of all eligible initiated tasks in a matured start cohort; a conservative confirmed-success share, not observed failure rate.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct matured task_ids with valid independent task.accepted evidence by as_of |
| Denominator | All distinct eligible task_ids started in window with started_at + preregistered task_observation_hours &lt;= as_of |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Tasks in a preregistered workflow cohort, started in window; each counted once across retries, skills and clients. |
| Exclusions | Cancelled before start, sandbox/evaluation tasks and out-of-scope workflows; never post-start failures/abandonments. |
| Events and source | task.started; task.accepted; task.failed; task.abandoned; task.cancelled; work-management acceptance record |
| Owner / cadence | Quality Engineering / Weekly pilot; monthly departmental outcome review |
| Missing evidence | Unresolved/missing terminal outcomes remain in denominator with unknown count and known-outcome coverage; do not label them failed. Invalid/missing start excluded from calculation but flagged as orphan evidence. |
| Gaming and limits | Split easy tasks or omit starts; reconcile starts to approved backlog and audit acceptance rubrics. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Maturation horizon is workflow-specific and must be approved; no automatic abandonment on timeout. |
### Skill selection precision
Correct activations among activations on an independently labeled evaluation corpus.
| Contract | Definition |
| --- | --- |
| Numerator | True-positive activations for the requested workflow |
| Denominator | True-positive plus false-positive activations |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | All candidate/client labeled evaluation task-trials with known activation and relevance. |
| Exclusions | Unlabeled/unknown activations excluded with coverage; no cherry-picked failed trials. |
| Events and source | eval.selection; versioned labeled corpus and runner |
| Owner / cadence | Data & AI / Each skill/client qualification |
| Missing evidence | Unknown activation/relevance is unscorable; publish missing count and deny qualification if planned coverage incomplete. |
| Gaming and limits | Choose easy labels or hide negative cases; freeze corpus and independently review labels. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Does not show execution success; precision depends on corpus prevalence. |
### Skill selection recall
Relevant task-trials in which the intended skill activates.
| Contract | Definition |
| --- | --- |
| Numerator | True-positive activations |
| Denominator | True-positive plus false-negative task-trials |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Independently labeled relevant evaluation task-trials for a skill/client tuple. |
| Exclusions | Irrelevant tasks; missing relevance or activation reported as unscorable, not negative. |
| Events and source | eval.selection; versioned labeled corpus and runner |
| Owner / cadence | Data & AI / Each skill/client qualification |
| Missing evidence | Report evaluation coverage; null if no relevant labeled tasks. |
| Gaming and limits | Overtrigger to maximize recall; always pair with precision and negative cases. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Loading the right skill is not adherence. |
### Supported bundle coverage
Inventoried active installations with verified effective approved, supported and nonrevoked bundle/adapter tuple.
| Contract | Definition |
| --- | --- |
| Numerator | Eligible installation_ids with valid inventory evidence within approved freshness window and matching support matrix |
| Denominator | All expected active installation_ids in the managed pilot inventory |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Active installation inventory frozen for report, including invisible/offline entries until authoritative offboarding. |
| Exclusions | Verified decommissioned installations and nonpilot assets; lack of telemetry alone never excludes. |
| Events and source | inventory.observed; catalog.published; catalog.revoked; device inventory |
| Owner / cadence | Platform & IT / Weekly and at revocation |
| Missing evidence | Unknown/stale versions count outside numerator, inside denominator. Show inventory discovery coverage versus eligible device roster; if roster unknown metric is provisional. |
| Gaming and limits | Remove silent devices or trust declared versions; reconcile managed inventory and separately label attestation trust. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Even verified file digests do not prove a private model followed the content. |
### Approved-workflow adoption
Eligible participants with at least one approved-skill workflow use; usefulness assessed separately through accepted outcomes and feedback.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct eligible pseudonymous participants with workflow-linked skill.used on approved revision |
| Denominator | Distinct eligible participants in frozen invited cohort |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Consented or otherwise lawfully enrolled pilot cohort for the period; supported workflow available. |
| Exclusions | Outside pilot and formally recorded leave before period; nonresponders remain eligible, not excluded. |
| Events and source | skill.used; cohort.snapshot; optional qualified client adapter or declaration |
| Owner / cadence | Data & AI / Monthly |
| Missing evidence | Show observed lower bound and telemetry/response coverage; missing usage unknown rather than non-use. |
| Gaming and limits | Invocation quotas and coercion; no target usage count, split server/client/self-report origins. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Self-report is not verified use; installation/loading is not use or benefit. Suppress small groups. |
### Change lead time
Arithmetic mean commit-to-first-successful-production-deployment duration; also publish median/p90 and sample count.
| Contract | Definition |
| --- | --- |
| Numerator | Sum of elapsed hours from committed_at to first successful production deployment for each service+commit |
| Denominator | Count of eligible service+commit pairs with valid mappings |
| Expression | N / D |
| Aggregation | mean |
| Unit | hours/change |
| Eligible population | Changes first successfully deployed to a service in reporting window; rollout retries collapse to same logical deployment. |
| Exclusions | Nonproduction, duplicates, no-op deployment with no new commits; missing mappings shown as coverage loss. |
| Events and source | change.committed; deployment.completed; VCS immutable commit timestamps and release manifest |
| Owner / cadence | Platform & IT / Weekly per service |
| Missing evidence | Missing commit mapping or negative/skewed duration excluded from numeric sample, reported explicitly; no zero substitution. |
| Gaming and limits | Timestamp rewriting and cherry-picking fast work; lock change mapping and show undeployed backlog age. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Not PR cycle time, effort saved, or a complete view of unfinished changes. p90 uses nearest-rank sorted sample. |
### Deployment frequency
Distinct successful logical production deployments per complete service-day of observation.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct service_id+deployment_id successful production deployments in window |
| Denominator | Observed service-days in window |
| Expression | N / D |
| Aggregation | ratio |
| Unit | deployments/service-day |
| Eligible population | Declared production services and complete UTC observation days; report each service before pooled views. |
| Exclusions | Test/staging, failed attempts without production effect, duplicate callbacks and retries of the same rollout. |
| Events and source | deployment.completed; authoritative deployment service |
| Owner / cadence | Platform & IT / Weekly per service |
| Missing evidence | Missing feed periods not zero; report coverage and no unqualified overall rate when period incomplete. |
| Gaming and limits | Split deployments without value; pair with success, rework and failure measures. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. More deployments alone do not establish better performance; affected unsuccessful changes remain in change-fail population. |
### Change fail rate
Production deployment effects requiring unplanned remediation, rollback or hotfix, not solely outage declarations.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct matured production deployment_ids linked to qualifying immediate intervention |
| Denominator | All distinct production deployment_ids that reached production in the matured deployment cohort |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Deployments with production effect during window and approved intervention follow-up horizon elapsed. |
| Exclusions | Failed preproduction attempts, duplicate callbacks and no-effect retries; failures after production effect stay included. |
| Events and source | deployment.completed; deployment.failed; incident.linked; release and incident records |
| Owner / cadence | Quality Engineering / Weekly; finalized after horizon |
| Missing evidence | Known failures / all eligible deployments is a lower bound where incident linkage incomplete; label provisional and report unknown links. |
| Gaming and limits | Avoid incident links or relabel intervention planned; reconcile rollbacks/hotfixes independently. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Define immediate intervention and follow-up horizon before pilot; no universal incident-to-AI attribution. |
### Failed deployment recovery time
Mean elapsed time from production deployment failure onset to service restoration, with median/p90 and unresolved count/age.
| Contract | Definition |
| --- | --- |
| Numerator | Sum of recovery_at minus failure_started_at in hours for recovered eligible deployment failures |
| Denominator | Count of recovered eligible deployment failures with valid timestamps |
| Expression | N / D |
| Aggregation | mean |
| Unit | hours/failure |
| Eligible population | Production deployment failures beginning in window; latest verified restoration if a recovery is rescinded. |
| Exclusions | Nondeployment incidents; invalid timestamp pairs reported missing, not treated as instantaneous recovery. |
| Events and source | deployment.failed; service.restored; incident service |
| Owner / cadence | Platform & IT / Weekly with unresolved failures |
| Missing evidence | Unresolved failures reported separately and excluded only from recovered-duration distribution; prevent declaring improvement without their visibility. |
| Gaming and limits | Premature recovery declarations or omit hard cases; require operational readback and carry unresolved ages. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Not all-incident MTTR; recovered-only sample has survivorship bias. p90 nearest rank. |
### Deployment rework rate
Unplanned production deployment effects triggered by a production incident as a share of deployment effects.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct incident-linked deployment_ids classified unplanned remediation |
| Denominator | All distinct production deployment_ids with production effect in window |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Production deployment effects in window with immutable planned/unplanned classification and incident linkage. |
| Exclusions | Nonproduction, no-effect retries and duplicates; do not exclude unclassified changes silently. |
| Events and source | deployment.completed; incident.linked; release intent classification |
| Owner / cadence | Platform & IT / Weekly |
| Missing evidence | Unknown classification stays denominator; observed numerator is lower bound until reconciliation; show classification coverage. |
| Gaming and limits | Call hotfixes planned; freeze reason and independently reconcile incident/deployment links. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Distinct from failure rate: one failed deployment can lead to multiple separate rework deployments. |
### Changes with escaped quality issues
Accepted changes with at least one confirmed post-acceptance defect during approved follow-up, split by severity.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct eligible change_ids with one or more linked confirmed defects in follow-up |
| Denominator | Accepted change_ids with completed predeclared follow-up horizon |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Accepted changes in acceptance window whose follow-up is complete by as_of. |
| Exclusions | Immature changes shown separately; duplicates/unconfirmed reports excluded but counted as pending triage. |
| Events and source | change.accepted; defect.confirmed; defect tracking and acceptance evidence |
| Owner / cadence | Quality Engineering / Monthly mature cohorts |
| Missing evidence | Unknown linkage is a coverage warning; no fabricated clean outcome. Show absolute defect and severe incident counts as well. |
| Gaming and limits | Shorten follow-up or downgrade severity; freeze horizon and rubric and independently sample defects. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Counts affected changes, not raw defects per change; no presumption defects are AI-caused. |
### Confirmed policy effects
Eligible evaluated attempts with an actual confirmed prohibited effect; report attempts, blocked attempts and effects separately.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct attempt_ids with confirmed prohibited action effect |
| Denominator | All evaluated eligible attempt_ids including failed and abandoned runs |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Governed skill trials or supported workflow attempts, reported separately for eval and live populations. |
| Exclusions | Out-of-scope runs; detection gaps remain coverage issues, not exclusions from known initiated population. |
| Events and source | attempt.started; policy.violation; gate.blocked; security audit and incident triage |
| Owner / cadence | Architecture & Security / Immediate incident action; weekly aggregates |
| Missing evidence | Unknown outcomes remain visible; zero detected effects never proves safety. Missing audits make rate provisional. |
| Gaming and limits | Hide incidents or inflate harmless trials; absolute severity counts and fixed task mix accompany rate. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Blocked attempts are not actual effects; any critical effect blocks promotion regardless of aggregate rate. |
### Cost per accepted outcome
Allocated total workflow cost including unsuccessful attempts, licenses, compute, tooling and human review/rework divided by accepted outcomes.
| Contract | Definition |
| --- | --- |
| Numerator | Sum allocated costs in one approved reporting currency for all tasks/attempts in matured start cohort |
| Denominator | Distinct independently accepted tasks in same cohort |
| Expression | N / D |
| Aggregation | ratio |
| Unit | currency/accepted outcome |
| Eligible population | Matured eligible started-task cohort, with all attempt costs through as_of and allocated shared period costs. |
| Exclusions | Unrelated projects and documented taxes/transfers outside chosen accounting basis; never failed/abandoned attempts. |
| Events and source | cost.recorded; task.accepted; finance invoices, usage ledger, sampled effort with approved rates |
| Owner / cadence | Finance & Accounting Squad / Monthly with late invoice restatement |
| Missing evidence | Missing cost buckets produce partial estimate plus coverage, not a total. Mixed currency requires dated approved conversion; zero accepted outcomes = null with full cost shown. |
| Gaming and limits | Count tokens only or hide labor/failures; reconcile invoice and allocation totals without double counting. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Allocation and sampled labor carry uncertainty; no ROI without independently measured business benefit. |
### Verification confidence and cognitive load
Three separate anonymous 1–5 item distributions: confidence in verifying output, manageable workload, usefulness. Primary item: verification confidence mean; report full distributions and response rate.
| Contract | Definition |
| --- | --- |
| Numerator | Sum valid 1–5 verification-confidence responses, one per participant per survey wave |
| Denominator | Count valid responses to that item |
| Expression | N / D |
| Aggregation | mean |
| Unit | points (1–5) |
| Eligible population | Invited eligible cohort at fixed survey wave; voluntary responses. |
| Exclusions | Invalid/out-of-range answers and superseded duplicate submission; nonresponders stay in response-rate denominator. |
| Events and source | survey.response; anonymous survey with single-use token and aggregate invitation count |
| Owner / cadence | People & Administration Squad / After pilot workflow cycle; periodic follow-up |
| Missing evidence | Report valid response count / invited count and item nonresponse; no imputation. Suppress people cohorts below five. |
| Gaming and limits | Pressure to respond positively; no manager access to individual responses, avoid identifying free text. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Perception and selection bias; not measured time savings. No composite productivity index. |
### Skills within substantive review window
Active approved skill revisions with an accountable owner and completed substantive review not past due.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct active approved skill revisions with current owner, review evidence and review_due_at &gt;= as_of |
| Denominator | All active approved skill revisions in catalog snapshot |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Approved revisions currently supported for use at as_of. |
| Exclusions | Experimental and retired revisions; deprecated/revoked in-use counts reported independently, not hidden. |
| Events and source | catalog.published; catalog.reviewed; catalog.deprecated; catalog.revoked; version inventory |
| Owner / cadence | Data & AI / Monthly and each release |
| Missing evidence | Missing owner/date/evidence outside numerator; show ownerless, deprecated-in-use and revoked-in-use absolute counts. |
| Gaming and limits | Rubber-stamp review dates; require linked regression/security/usefulness evidence. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. A current review is not proof of effectiveness; consumer inventory may miss shadow copies. |
### Workflow-specific business acceptance
Independently accepted domain outcomes against a predeclared business rubric, separate from technical completion.
| Contract | Definition |
| --- | --- |
| Numerator | Eligible completed-observation task_ids meeting the department-specific outcome rubric |
| Denominator | All eligible initiated workflow task_ids with matured business-outcome horizon |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | One named departmental workflow and predeclared start cohort; never pool unlike rubrics. |
| Exclusions | Cancelled-before-start and unrelated workflows; unsuccessful or abandoned eligible work remains. |
| Events and source | task.started; business.accepted; departmental case/content/reconciliation/onboarding review record |
| Owner / cadence | Product Management / Each pilot cycle with owning department |
| Missing evidence | Unknown follow-up stays denominator with unresolved count; no claim actual business outcome changed without source evidence. |
| Gaming and limits | Weaken rubric or count drafts as customer benefit; lock rubric and independently audit acceptance. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Domain owner signs acceptance: Operations service accuracy; Marketing claims/rights; Finance reconciliation accuracy; HR policy correctness; Product usability/value. Not revenue uplift. |
</details>
<details>
<summary>Run the nine-metric synthetic prototype and inspect omissions</summary>
## Run the synthetic measurement example
**Executed synthetic example — not Eldorado results.** The bundled fixture produces 1 independently accepted task from 4 matured starts: 25% confirmed success. One unresolved task remains in that denominator; known-outcome coverage is 75%. Selection precision and recall are each 1 / 2 = 50%. Allocated synthetic cost is EUR 60 / 1 accepted outcome = EUR 60 per accepted outcome. These deliberately small samples demonstrate arithmetic and missingness, not a baseline, target or ROI claim.
From the private documentation checkout, run `node scripts/ai-kpi.mjs` and `node --test scripts/ai-kpi.test.mjs`. The fixture `scripts/fixtures/ai-kpi-synthetic.json` is labeled synthetic; every result carries the same label and calculation version. This prototype has no network collectors and does not enable employee telemetry.
The executable covers validated success, selection precision/recall, change fail and rework rates, escaped quality, policy effects, cost and human experience. Other catalog metrics remain contracts rather than implemented collectors; output lists the omissions. Snapshot inputs are simplified, pre-reconciled records, not a production ingestion system. Conflicting duplicates reject the calculation rather than silently choosing a value.
</details>
**Next:** [Use findings to maintain, quarantine or replace skills →](./skills-maintenance.mdx)
</div>
@@ -0,0 +1,36 @@
---
id: approved-workflow-adoption
slug: /measurement/approved-workflow-adoption
title: Approved-workflow adoption
description: Definition, collection evidence and limitations for approved-workflow adoption.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Unimplemented metric — no live telemetry.** This is a prospective contract, not an implemented calculation or collector.
{/* contract:start */}
Eligible participants with at least one approved-skill workflow use; usefulness assessed separately through accepted outcomes and feedback.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct eligible pseudonymous participants with workflow-linked skill.used on approved revision |
| Denominator | Distinct eligible participants in frozen invited cohort |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Consented or otherwise lawfully enrolled pilot cohort for the period; supported workflow available. |
| Exclusions | Outside pilot and formally recorded leave before period; nonresponders remain eligible, not excluded. |
| Events and source | skill.used; cohort.snapshot; optional qualified client adapter or declaration |
| Owner / cadence | Data & AI / Monthly |
| Missing evidence | Show observed lower bound and telemetry/response coverage; missing usage unknown rather than non-use. |
| Gaming and limits | Invocation quotas and coercion; no target usage count, split server/client/self-report origins. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Self-report is not verified use; installation/loading is not use or benefit. Suppress small groups. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,36 @@
---
id: change-fail-rate
slug: /measurement/change-fail-rate
title: Change fail rate
description: Definition, collection evidence and limitations for change fail rate.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Prototype calculation — no live telemetry.** The synthetic example calculates this metric; it has no network collectors.
{/* contract:start */}
Production deployment effects requiring unplanned remediation, rollback or hotfix, not solely outage declarations.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct matured production deployment_ids linked to qualifying immediate intervention |
| Denominator | All distinct production deployment_ids that reached production in the matured deployment cohort |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Deployments with production effect during window and approved intervention follow-up horizon elapsed. |
| Exclusions | Failed preproduction attempts, duplicate callbacks and no-effect retries; failures after production effect stay included. |
| Events and source | deployment.completed; deployment.failed; incident.linked; release and incident records |
| Owner / cadence | Quality Engineering / Weekly; finalized after horizon |
| Missing evidence | Known failures / all eligible deployments is a lower bound where incident linkage incomplete; label provisional and report unknown links. |
| Gaming and limits | Avoid incident links or relabel intervention planned; reconcile rollbacks/hotfixes independently. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Define immediate intervention and follow-up horizon before pilot; no universal incident-to-AI attribution. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,36 @@
---
id: change-lead-time
slug: /measurement/change-lead-time
title: Change lead time
description: Definition, collection evidence and limitations for change lead time.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Unimplemented metric — no live telemetry.** This is a prospective contract, not an implemented calculation or collector.
{/* contract:start */}
Arithmetic mean commit-to-first-successful-production-deployment duration; also publish median/p90 and sample count.
| Contract | Definition |
| --- | --- |
| Numerator | Sum of elapsed hours from committed_at to first successful production deployment for each service+commit |
| Denominator | Count of eligible service+commit pairs with valid mappings |
| Expression | N / D |
| Aggregation | mean |
| Unit | hours/change |
| Eligible population | Changes first successfully deployed to a service in reporting window; rollout retries collapse to same logical deployment. |
| Exclusions | Nonproduction, duplicates, no-op deployment with no new commits; missing mappings shown as coverage loss. |
| Events and source | change.committed; deployment.completed; VCS immutable commit timestamps and release manifest |
| Owner / cadence | Platform & IT / Weekly per service |
| Missing evidence | Missing commit mapping or negative/skewed duration excluded from numeric sample, reported explicitly; no zero substitution. |
| Gaming and limits | Timestamp rewriting and cherry-picking fast work; lock change mapping and show undeployed backlog age. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Not PR cycle time, effort saved, or a complete view of unfinished changes. p90 uses nearest-rank sorted sample. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,36 @@
---
id: changes-with-escaped-quality-issues
slug: /measurement/changes-with-escaped-quality-issues
title: Changes with escaped quality issues
description: Definition, collection evidence and limitations for changes with escaped quality issues.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Prototype calculation — no live telemetry.** The synthetic example calculates this metric; it has no network collectors.
{/* contract:start */}
Accepted changes with at least one confirmed post-acceptance defect during approved follow-up, split by severity.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct eligible change_ids with one or more linked confirmed defects in follow-up |
| Denominator | Accepted change_ids with completed predeclared follow-up horizon |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Accepted changes in acceptance window whose follow-up is complete by as_of. |
| Exclusions | Immature changes shown separately; duplicates/unconfirmed reports excluded but counted as pending triage. |
| Events and source | change.accepted; defect.confirmed; defect tracking and acceptance evidence |
| Owner / cadence | Quality Engineering / Monthly mature cohorts |
| Missing evidence | Unknown linkage is a coverage warning; no fabricated clean outcome. Show absolute defect and severe incident counts as well. |
| Gaming and limits | Shorten follow-up or downgrade severity; freeze horizon and rubric and independently sample defects. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Counts affected changes, not raw defects per change; no presumption defects are AI-caused. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,42 @@
---
id: collection-and-safeguards
slug: /measurement/collection-and-safeguards
title: Collection and safeguards
description: Shared interpretation rules, event contracts and privacy safeguards for selected metrics.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** Registry inclusion does not require use, collection or baselining. All owner and cadence entries are proposals to confirm for selected metrics, not assigned responsibilities or approved schedules.
{/* preserved:start */}
Introduction depends on the [roadmap gates](../roadmap.mdx); these pages do not describe installed controls or measured company results.
### Decide what counts before counting
Use the [metric definitions](./index.mdx#metric-definitions) for exact definitions. Every report states its eligible population, observation window, numerator and denominator or distribution sample count, source coverage, exclusions and calculation version. Zero denominators return “not available.” Missing telemetry is unknown, not inactivity, compliance or success. Examples are explicitly synthetic and illustrative.
Begin with task acceptance, repository, CI, deployment and incident systems because they can independently establish outcomes. Add catalog/version inventory and task-level declarations. Client telemetry is supplementary and version-dependent; enabling rich tool details may collect sensitive commands and identifiers. Do not enable it merely to count skills. A normalized adapter may report approved skill identifiers without forwarding raw arguments.
Validated success uses all eligible initiated tasks whose predeclared observation window has matured. Failed and abandoned tasks remain nonsuccess. Unresolved or unobserved outcomes remain in the denominator, with known-outcome coverage shown alongside the conservative confirmed-success share. They are not relabeled as observed failure. A task cancelled before start is excluded; cancellation after start remains visible. Count a task once across retries and multiple skills. For timeliness, also show unfinished work and age; accepted-only lead-time distributions have survivorship limitations.
The registry includes five service-level DORA measures: commit-to-production lead time, deployment frequency, change fail rate, failed deployment recovery time and deployment rework rate. Select them only where applicable; do not substitute PR-open-to-merge time or all-incident MTTR. Where relevant, interpret them alongside selected quality, policy, cost, support, adoption, experience or maintenance evidence. Keep customer/business outcomes linked to their departmental hypotheses; do not infer conversion, trust or revenue improvement from delivery telemetry.
### Interpretation limits {#baseline-and-interpretation}
See [Baseline](../baseline.mdx) for selecting relevant metrics and establishing comparable current-practice evidence. Pilot application belongs to [Adoption](../skills-adoption.mdx); ongoing reporting belongs to [Maintenance](../skills-maintenance.mdx).
Elapsed time and human effort are different quantities. Parallel agents may reduce waiting while increasing review or compute. Include failed attempts and human review/rework in cost, do not multiply a multi-skill task's value across every invocation, and do not convert survey perceptions into proven time savings. Small or incomplete populations yield evidence limits, not an ROI percentage.
### Event and privacy contract
Use a versioned event envelope and required fields per event. Source producer plus event ID deduplicates transport retries. Conflicting payloads under the same key are quarantined. Attempts have distinct IDs under one task. Domain IDs deduplicate deployments, defects and approvals even when multiple feeds describe them. Late arrivals produce versioned aggregate corrections; never silently overwrite a published result. Preserve occurrence and receipt times, reject impossible orderings and flag clock skew. Missing terminal events remain unresolved until the work owner reconciles them.
Many-to-many task/attempt/skill/client associations preserve exact immutable versions. Unknown version stays null with a reason; never assign the latest revision retroactively. Client declarations, server facts and self-reports remain separately labeled. A skill-loaded event is evidence of loading only. The minimal prototype can operate without actor identity except where a lawful, necessary adoption denominator requires pseudonymous cohort membership.
The privacy starting proposal is 30 days for raw structured analytics events and 12 months for aggregated trends, subject to the responsible owners' review. Keep the approved catalog/approval record for the supported revision's lifetime and its required audit period, which must be decided separately. Incident evidence uses a restricted, explicitly authorized hold and deletion schedule, not an indefinite analytics exception. Suppress reports below five people and prohibit drill-down or overlapping cohort slices that reconstruct identities. Five is a proposed minimum, not a guarantee against re-identification. No raw prompts, code, screens, customer cases or secrets are collected by default. Publish the purpose, lawful collection basis, access/deletion route and retention before collecting. Consent is not presumed to be an appropriate employment-law basis.
{/* preserved:end */}
Return to the [Skills Measurement index](./index.mdx) for every metric definition.
</div>
@@ -0,0 +1,36 @@
---
id: confirmed-policy-effects
slug: /measurement/confirmed-policy-effects
title: Confirmed policy effects
description: Definition, collection evidence and limitations for confirmed policy effects.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Prototype calculation — no live telemetry.** The synthetic example calculates this metric; it has no network collectors.
{/* contract:start */}
Eligible evaluated attempts with an actual confirmed prohibited effect; report attempts, blocked attempts and effects separately.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct attempt_ids with confirmed prohibited action effect |
| Denominator | All evaluated eligible attempt_ids including failed and abandoned runs |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Governed skill trials or supported workflow attempts, reported separately for eval and live populations. |
| Exclusions | Out-of-scope runs; detection gaps remain coverage issues, not exclusions from known initiated population. |
| Events and source | attempt.started; policy.violation; gate.blocked; security audit and incident triage |
| Owner / cadence | Architecture & Security / Immediate incident action; weekly aggregates |
| Missing evidence | Unknown outcomes remain visible; zero detected effects never proves safety. Missing audits make rate provisional. |
| Gaming and limits | Hide incidents or inflate harmless trials; absolute severity counts and fixed task mix accompany rate. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Blocked attempts are not actual effects; any critical effect blocks promotion regardless of aggregate rate. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,36 @@
---
id: cost-per-accepted-outcome
slug: /measurement/cost-per-accepted-outcome
title: Cost per accepted outcome
description: Definition, collection evidence and limitations for cost per accepted outcome.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Prototype calculation — no live telemetry.** The synthetic example calculates this metric; it has no network collectors.
{/* contract:start */}
Allocated total workflow cost including unsuccessful attempts, licenses, compute, tooling and human review/rework divided by accepted outcomes.
| Contract | Definition |
| --- | --- |
| Numerator | Sum allocated costs in one approved reporting currency for all tasks/attempts in matured start cohort |
| Denominator | Distinct independently accepted tasks in same cohort |
| Expression | N / D |
| Aggregation | ratio |
| Unit | currency/accepted outcome |
| Eligible population | Matured eligible started-task cohort, with all attempt costs through as_of and allocated shared period costs. |
| Exclusions | Unrelated projects and documented taxes/transfers outside chosen accounting basis; never failed/abandoned attempts. |
| Events and source | cost.recorded; task.accepted; finance invoices, usage ledger, sampled effort with approved rates |
| Owner / cadence | Finance & Accounting Squad / Monthly with late invoice restatement |
| Missing evidence | Missing cost buckets produce partial estimate plus coverage, not a total. Mixed currency requires dated approved conversion; zero accepted outcomes = null with full cost shown. |
| Gaming and limits | Count tokens only or hide labor/failures; reconcile invoice and allocation totals without double counting. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Allocation and sampled labor carry uncertainty; no ROI without independently measured business benefit. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,36 @@
---
id: deployment-frequency
slug: /measurement/deployment-frequency
title: Deployment frequency
description: Definition, collection evidence and limitations for deployment frequency.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Unimplemented metric — no live telemetry.** This is a prospective contract, not an implemented calculation or collector.
{/* contract:start */}
Distinct successful logical production deployments per complete service-day of observation.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct service_id+deployment_id successful production deployments in window |
| Denominator | Observed service-days in window |
| Expression | N / D |
| Aggregation | ratio |
| Unit | deployments/service-day |
| Eligible population | Declared production services and complete UTC observation days; report each service before pooled views. |
| Exclusions | Test/staging, failed attempts without production effect, duplicate callbacks and retries of the same rollout. |
| Events and source | deployment.completed; authoritative deployment service |
| Owner / cadence | Platform & IT / Weekly per service |
| Missing evidence | Missing feed periods not zero; report coverage and no unqualified overall rate when period incomplete. |
| Gaming and limits | Split deployments without value; pair with success, rework and failure measures. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. More deployments alone do not establish better performance; affected unsuccessful changes remain in change-fail population. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,36 @@
---
id: deployment-rework-rate
slug: /measurement/deployment-rework-rate
title: Deployment rework rate
description: Definition, collection evidence and limitations for deployment rework rate.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Prototype calculation — no live telemetry.** The synthetic example calculates this metric; it has no network collectors.
{/* contract:start */}
Unplanned production deployment effects triggered by a production incident as a share of deployment effects.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct incident-linked deployment_ids classified unplanned remediation |
| Denominator | All distinct production deployment_ids with production effect in window |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Production deployment effects in window with immutable planned/unplanned classification and incident linkage. |
| Exclusions | Nonproduction, no-effect retries and duplicates; do not exclude unclassified changes silently. |
| Events and source | deployment.completed; incident.linked; release intent classification |
| Owner / cadence | Platform & IT / Weekly |
| Missing evidence | Unknown classification stays denominator; observed numerator is lower bound until reconciliation; show classification coverage. |
| Gaming and limits | Call hotfixes planned; freeze reason and independently reconcile incident/deployment links. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Distinct from failure rate: one failed deployment can lead to multiple separate rework deployments. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,36 @@
---
id: failed-deployment-recovery-time
slug: /measurement/failed-deployment-recovery-time
title: Failed deployment recovery time
description: Definition, collection evidence and limitations for failed deployment recovery time.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Unimplemented metric — no live telemetry.** This is a prospective contract, not an implemented calculation or collector.
{/* contract:start */}
Mean elapsed time from production deployment failure onset to service restoration, with median/p90 and unresolved count/age.
| Contract | Definition |
| --- | --- |
| Numerator | Sum of recovery_at minus failure_started_at in hours for recovered eligible deployment failures |
| Denominator | Count of recovered eligible deployment failures with valid timestamps |
| Expression | N / D |
| Aggregation | mean |
| Unit | hours/failure |
| Eligible population | Production deployment failures beginning in window; latest verified restoration if a recovery is rescinded. |
| Exclusions | Nondeployment incidents; invalid timestamp pairs reported missing, not treated as instantaneous recovery. |
| Events and source | deployment.failed; service.restored; incident service |
| Owner / cadence | Platform & IT / Weekly with unresolved failures |
| Missing evidence | Unresolved failures reported separately and excluded only from recovered-duration distribution; prevent declaring improvement without their visibility. |
| Gaming and limits | Premature recovery declarations or omit hard cases; require operational readback and carry unresolved ages. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Not all-incident MTTR; recovered-only sample has survivorship bias. p90 nearest rank. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
+72
View File
@@ -0,0 +1,72 @@
---
id: index
slug: /measurement
title: Skills Measurement
sidebar_label: Measurement
description: Optional contracts for workflow effectiveness and skills effectiveness and health, with distinct populations and honest implementation limits.
pagination_prev: stage-01-skills-adoption
pagination_next: baseline
hide_table_of_contents: true
---
import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
<div className="strategy-content">
Start with how work performs today; compare relevant outcomes after introducing skills. Separately assess whether the skills are effective, supported, used and maintained. Registry inclusion does not require a metric to be used, collected or baselined. More adoption does not prove improved work.
<ArchifyDiagram name="strategy-measurement" title="Workflow effectiveness / Skills effectiveness & health" story />
**Target operating model — candidate definitions, not installed telemetry or a collection plan.** Proposed owners and cadences in the contracts apply only if selected and agreed for a workflow.
## Read a candidate contract
Each entry explains meaning and applicability, calculation, required inputs and evidence, exclusions, missing-evidence behavior, limitations and implementation status. The two groups below classify every contract by its primary question; conditional reuse never merges populations. A delivery metric need not fit a non-delivery workflow.
To select a relevant subset and establish actual starting evidence, use [Baseline](../baseline.mdx). Pilot application belongs to [Adoption](../skills-adoption.mdx); ongoing interpretation belongs to [Maintenance](../skills-maintenance.mdx).
## Metric definitions
There are **16 contracts: 9 prototype calculations and 7 unimplemented metrics**. The prototype has no network collectors. None of these counts establishes live telemetry.
The nine calculations cover task success, selection precision and recall, change fail rate, deployment rework, escaped quality, policy effects, cost and the primary human-experience item. The seven omissions are supported bundle coverage, approved-workflow adoption, change lead time, deployment frequency, failed deployment recovery time, substantive-review coverage and workflow-specific business acceptance.
Each contract is a prospective definition, not a rollout obligation. No live source or observed baseline is established. N and D refer to the numerator and denominator shown for that metric.
### Workflow effectiveness
**Is the work getting better?** Baseline relevant current-workflow outcomes even before standardized skills exist, then compare the same outcomes during adoption and maintenance. Use comparable task mix, acceptance rules, follow-up periods and source coverage. Before/after trends alone are not causal evidence of a skills benefit.
1. [Validated task success](./validated-task-success.mdx) — **Prototype calculation.** Independently accepted outcomes among matured workflow starts; failures, abandonment and unresolved outcomes remain in the denominator.
2. [Change lead time](./change-lead-time.mdx) — **Unimplemented metric.** Delivery time for production changes in one service, not general task duration.
3. [Deployment frequency](./deployment-frequency.mdx) — **Unimplemented metric.** Production delivery frequency for one service; frequency alone is not value.
4. [Change fail rate](./change-fail-rate.mdx) — **Prototype calculation.** Production deployments causing failures; requires joined change/incident evidence.
5. [Failed deployment recovery time](./failed-deployment-recovery-time.mdx) — **Unimplemented metric.** Recovery from failed production deployments; conditional on eligible incidents.
6. [Deployment rework rate](./deployment-rework-rate.mdx) — **Prototype calculation.** Unplanned corrective production deployments, not all forms of task rework.
7. [Changes with escaped quality issues](./changes-with-escaped-quality-issues.mdx) — **Prototype calculation.** Accepted changes with confirmed downstream issues after follow-up.
8. [Confirmed policy effects](./confirmed-policy-effects.mdx) — **Prototype calculation.** Safety of supported workflow attempts; governed skill trials are a separate evaluation population, never pooled with live work.
9. [Cost per accepted outcome](./cost-per-accepted-outcome.mdx) — **Prototype calculation.** Cost of the matured workflow cohort, including unsuccessful attempts and recorded review/rework effort. Missing cost buckets remain partial.
10. [Verification confidence and cognitive load](./verification-confidence-and-cognitive-load.mdx) — **Prototype calculation.** Anonymous cohort experience: confidence, workload and usefulness separately, not measured time savings.
11. [Workflow-specific business acceptance](./workflow-specific-business-acceptance.mdx) — **Unimplemented metric.** Acceptance against an agreed departmental rubric; requires a defined workflow and independent evidence.
Human effort is recorded as review/rework inputs where the cost contract supports it; the experience survey describes perception. Neither elapsed delivery time nor token counts establish effort saved. If the current workflow lacks the event semantics required by a contract (for example, governed attempts), record it as not applicable or unavailable with a reason; do not relabel unrelated records to manufacture a baseline.
### Skills effectiveness & health
**Are the skills fit for use and kept fit?** Qualify named skills and versions, observe supported use during adoption, and review or retire them in maintenance. Without applicable skills, bundles or enrolled use, skill-specific measures may be **N/A, not zero**. Once a population exists, missing observations are unknown, not evidence of non-use or good health.
1. [Skill selection precision](./skill-selection-precision.mdx) — **Prototype calculation.** Did the evaluated selection choose an applicable skill? Requires labeled qualification cases.
2. [Skill selection recall](./skill-selection-recall.mdx) — **Prototype calculation.** Were expected skills selected? Requires the same labeled qualification population.
3. [Supported bundle coverage](./supported-bundle-coverage.mdx) — **Unimplemented metric.** Are expected active installations on supported, non-revoked bundles/adapters?
4. [Approved-workflow adoption](./approved-workflow-adoption.mdx) — **Unimplemented metric.** Is the enrolled cohort using approved skills in eligible workflows? Installation/loading is not use.
5. [Skills within substantive review window](./skills-within-substantive-review-window.mdx) — **Unimplemented metric.** Do active approved revisions have current owners and substantive review evidence?
**Task-success population matters.** The canonical validated-task-success contract above measures workflow outcomes, not an evaluation benchmark. A named skill/version can be examined as a predeclared live-workflow slice under that same contract, without counting retries or multiple skills as extra tasks or attributing causality. Sandbox/evaluation cases remain excluded: a named skill/version evaluation must be reported separately with its own declared cases, acceptance evidence and limits. It is not an additional implemented calculation or a second conflicting task-success formula. The canonical page explains this boundary. Likewise, keep policy-effect evaluation trials separate from live attempts.
Use both tracks together to decide whether to improve, retain or retire a skill. Higher selection scores, wider adoption or current reviews cannot substitute for accepted work, safety, cost and human experience.
Read [Collection and safeguards](./collection-and-safeguards.mdx) for shared interpretation, event and privacy rules. [Run the synthetic measurement example](./synthetic-example.mdx) for reproducible arithmetic and limits.
**Next:** [Establish a relevant workflow baseline →](../baseline.mdx)
</div>
@@ -0,0 +1,36 @@
---
id: skill-selection-precision
slug: /measurement/skill-selection-precision
title: Skill selection precision
description: Definition, collection evidence and limitations for skill selection precision.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Prototype calculation — no live telemetry.** The synthetic example calculates this metric; it has no network collectors.
{/* contract:start */}
Correct activations among activations on an independently labeled evaluation corpus.
| Contract | Definition |
| --- | --- |
| Numerator | True-positive activations for the requested workflow |
| Denominator | True-positive plus false-positive activations |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | All candidate/client labeled evaluation task-trials with known activation and relevance. |
| Exclusions | Unlabeled/unknown activations excluded with coverage; no cherry-picked failed trials. |
| Events and source | eval.selection; versioned labeled corpus and runner |
| Owner / cadence | Data & AI / Each skill/client qualification |
| Missing evidence | Unknown activation/relevance is unscorable; publish missing count and deny qualification if planned coverage incomplete. |
| Gaming and limits | Choose easy labels or hide negative cases; freeze corpus and independently review labels. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Does not show execution success; precision depends on corpus prevalence. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,36 @@
---
id: skill-selection-recall
slug: /measurement/skill-selection-recall
title: Skill selection recall
description: Definition, collection evidence and limitations for skill selection recall.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Prototype calculation — no live telemetry.** The synthetic example calculates this metric; it has no network collectors.
{/* contract:start */}
Relevant task-trials in which the intended skill activates.
| Contract | Definition |
| --- | --- |
| Numerator | True-positive activations |
| Denominator | True-positive plus false-negative task-trials |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Independently labeled relevant evaluation task-trials for a skill/client tuple. |
| Exclusions | Irrelevant tasks; missing relevance or activation reported as unscorable, not negative. |
| Events and source | eval.selection; versioned labeled corpus and runner |
| Owner / cadence | Data & AI / Each skill/client qualification |
| Missing evidence | Report evaluation coverage; null if no relevant labeled tasks. |
| Gaming and limits | Overtrigger to maximize recall; always pair with precision and negative cases. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Loading the right skill is not adherence. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,36 @@
---
id: skills-within-substantive-review-window
slug: /measurement/skills-within-substantive-review-window
title: Skills within substantive review window
description: Definition, collection evidence and limitations for skills within substantive review window.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Unimplemented metric — no live telemetry.** This is a prospective contract, not an implemented calculation or collector.
{/* contract:start */}
Active approved skill revisions with an accountable owner and completed substantive review not past due.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct active approved skill revisions with current owner, review evidence and review_due_at &gt;= as_of |
| Denominator | All active approved skill revisions in catalog snapshot |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Approved revisions currently supported for use at as_of. |
| Exclusions | Experimental and retired revisions; deprecated/revoked in-use counts reported independently, not hidden. |
| Events and source | catalog.published; catalog.reviewed; catalog.deprecated; catalog.revoked; version inventory |
| Owner / cadence | Data & AI / Monthly and each release |
| Missing evidence | Missing owner/date/evidence outside numerator; show ownerless, deprecated-in-use and revoked-in-use absolute counts. |
| Gaming and limits | Rubber-stamp review dates; require linked regression/security/usefulness evidence. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. A current review is not proof of effectiveness; consumer inventory may miss shadow copies. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,36 @@
---
id: supported-bundle-coverage
slug: /measurement/supported-bundle-coverage
title: Supported bundle coverage
description: Definition, collection evidence and limitations for supported bundle coverage.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Unimplemented metric — no live telemetry.** This is a prospective contract, not an implemented calculation or collector.
{/* contract:start */}
Inventoried active installations with verified effective approved, supported and nonrevoked bundle/adapter tuple.
| Contract | Definition |
| --- | --- |
| Numerator | Eligible installation_ids with valid inventory evidence within approved freshness window and matching support matrix |
| Denominator | All expected active installation_ids in the managed pilot inventory |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Active installation inventory frozen for report, including invisible/offline entries until authoritative offboarding. |
| Exclusions | Verified decommissioned installations and nonpilot assets; lack of telemetry alone never excludes. |
| Events and source | inventory.observed; catalog.published; catalog.revoked; device inventory |
| Owner / cadence | Platform & IT / Weekly and at revocation |
| Missing evidence | Unknown/stale versions count outside numerator, inside denominator. Show inventory discovery coverage versus eligible device roster; if roster unknown metric is provisional. |
| Gaming and limits | Remove silent devices or trust declared versions; reconcile managed inventory and separately label attestation trust. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Even verified file digests do not prove a private model followed the content. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,22 @@
---
id: synthetic-example
slug: /measurement/synthetic-example
title: Run the synthetic measurement example
description: Reproduce the synthetic KPI calculations and understand their limits.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
{/* preserved:start */}
**Executed synthetic example — not Eldorado results.** The bundled fixture produces 1 independently accepted task from 4 matured starts: 25% confirmed success. One unresolved task remains in that denominator; known-outcome coverage is 75%. Selection precision and recall are each 1 / 2 = 50%. Recorded synthetic compute cost is EUR 60 / 1 accepted outcome = EUR 60 per accepted outcome, a partial estimate: licenses, tooling, review and rework are missing. These deliberately small samples demonstrate arithmetic and missingness, not a baseline, target or ROI claim.
From the private documentation checkout, run `node scripts/ai-kpi.mjs` and `node --test scripts/ai-kpi.test.mjs`. The fixture `scripts/fixtures/ai-kpi-synthetic.json` is labeled synthetic; every result carries the same label and calculation version. This prototype has no network collectors and does not enable employee telemetry.
The executable covers validated success, selection precision/recall, change fail and rework rates, escaped quality, policy effects, cost and human experience. Other catalog metrics remain contracts rather than implemented collectors; output lists the omissions. Snapshot inputs are simplified, pre-reconciled records, not a production ingestion system. Conflicting duplicates reject the calculation rather than silently choosing a value.
{/* preserved:end */}
Return to the [Skills Measurement index](./index.mdx) for every metric definition.
</div>
@@ -0,0 +1,44 @@
---
id: validated-task-success
slug: /measurement/validated-task-success
title: Validated task success
description: Definition, collection evidence and limitations for validated task success.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Prototype calculation — no live telemetry.** The synthetic example calculates this metric; it has no network collectors.
{/* contract:start */}
Confirmed independently accepted tasks as a share of all eligible initiated tasks in a matured start cohort; a conservative confirmed-success share, not observed failure rate.
| Contract | Definition |
| --- | --- |
| Numerator | Distinct matured task_ids with valid independent task.accepted evidence by as_of |
| Denominator | All distinct eligible task_ids started in window with started_at + preregistered task_observation_hours &lt;= as_of |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | Tasks in a preregistered workflow cohort, started in window; each counted once across retries, skills and clients. |
| Exclusions | Cancelled before start, sandbox/evaluation tasks and out-of-scope workflows; never post-start failures/abandonments. |
| Events and source | task.started; task.accepted; task.failed; task.abandoned; task.cancelled; work-management acceptance record |
| Owner / cadence | Quality Engineering / Weekly pilot; monthly departmental outcome review |
| Missing evidence | Unresolved/missing terminal outcomes remain in denominator with unknown count and known-outcome coverage; do not label them failed. Invalid/missing start excluded from calculation but flagged as orphan evidence. |
| Gaming and limits | Split easy tasks or omit starts; reconcile starts to approved backlog and audit acceptance rubrics. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Maturation horizon is workflow-specific and must be approved; no automatic abandonment on timeout. |
{/* contract:end */}
## Workflow outcomes versus skill/version evaluation
This contract belongs to **Workflow effectiveness**. Use the same matured-start population and independent acceptance rules before and after introducing skills; skills are not required for a workflow outcome to exist. Do not narrow the later denominator to successful skill invocations.
For **Skills effectiveness & health**, a predeclared slice of live workflow tasks using a named skill/version may reuse this contract unchanged. Keep the parent cohort visible, report exact versions and selection limits, and count each task once across retries, skills and clients. Overlapping skill slices must not be summed. This is descriptive evidence, not proof that the skill caused success.
A sandbox or qualification evaluation of a named skill/version is a different population and remains excluded by this contract. Declare its cases, skill/version, client/model configuration, acceptance rubric and observed results separately; never combine those cases with live workflow starts or present their results as this prototype's workflow rate. This page does not introduce an implemented skill-evaluation metric or an alternative formula. No applicable skill means that skill-specific evaluation is N/A, not a zero workflow success rate.
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,36 @@
---
id: verification-confidence-and-cognitive-load
slug: /measurement/verification-confidence-and-cognitive-load
title: Verification confidence and cognitive load
description: Definition, collection evidence and limitations for verification confidence and cognitive load.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Prototype calculation — no live telemetry.** The synthetic example calculates this metric; it has no network collectors.
{/* contract:start */}
Three separate anonymous 1–5 item distributions: confidence in verifying output, manageable workload, usefulness. Primary item: verification confidence mean; report full distributions and response rate.
| Contract | Definition |
| --- | --- |
| Numerator | Sum valid 1–5 verification-confidence responses, one per participant per survey wave |
| Denominator | Count valid responses to that item |
| Expression | N / D |
| Aggregation | mean |
| Unit | points (1–5) |
| Eligible population | Invited eligible cohort at fixed survey wave; voluntary responses. |
| Exclusions | Invalid/out-of-range answers and superseded duplicate submission; nonresponders stay in response-rate denominator. |
| Events and source | survey.response; anonymous survey with single-use token and aggregate invitation count |
| Owner / cadence | People & Administration Squad / After pilot workflow cycle; periodic follow-up |
| Missing evidence | Report valid response count / invited count and item nonresponse; no imputation. Suppress people cohorts below five. |
| Gaming and limits | Pressure to respond positively; no manager access to individual responses, avoid identifying free text. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Perception and selection bias; not measured time savings. No composite productivity index. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
@@ -0,0 +1,36 @@
---
id: workflow-specific-business-acceptance
slug: /measurement/workflow-specific-business-acceptance
title: Workflow-specific business acceptance
description: Definition, collection evidence and limitations for workflow-specific business acceptance.
---
<div className="strategy-content">
**Target operating model — recommended contracts, not installed collection.** All owner and cadence entries below are proposals to confirm before the pilot, not assigned responsibilities or approved schedules.
**Unimplemented metric — no live telemetry.** This is a prospective contract, not an implemented calculation or collector.
{/* contract:start */}
Independently accepted domain outcomes against a predeclared business rubric, separate from technical completion.
| Contract | Definition |
| --- | --- |
| Numerator | Eligible completed-observation task_ids meeting the department-specific outcome rubric |
| Denominator | All eligible initiated workflow task_ids with matured business-outcome horizon |
| Expression | N / D * 100 |
| Aggregation | percent |
| Unit | % |
| Eligible population | One named departmental workflow and predeclared start cohort; never pool unlike rubrics. |
| Exclusions | Cancelled-before-start and unrelated workflows; unsuccessful or abandoned eligible work remains. |
| Events and source | task.started; business.accepted; departmental case/content/reconciliation/onboarding review record |
| Owner / cadence | Product Management / Each pilot cycle with owning department |
| Missing evidence | Unknown follow-up stays denominator with unresolved count; no claim actual business outcome changed without source evidence. |
| Gaming and limits | Weaken rubric or count drafts as customer benefit; lock rubric and independently audit acceptance. Descriptive signal, not causal AI productivity attribution. Source completeness, task mix and sampling limit inference; report uncertainty. Domain owner signs acceptance: Operations service accuracy; Marketing claims/rights; Finance reconciliation accuracy; HR policy correctness; Product usability/value. Not revenue uplift. |
{/* contract:end */}
Read the shared [collection and safeguards](./collection-and-safeguards.mdx) before collecting data; see the [synthetic example and limits](./synthetic-example.mdx).
Return to [Skills Measurement](./index.mdx).
</div>
+39 -41
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@@ -1,7 +1,7 @@
---
id: roadmap
title: Roadmap
description: Evidence-gated phases, no promised dates or budgets.
description: Build proven skills in human and AI Agent work, starting with Delivery, as the foundation for the future autonomous SDLC.
hide_table_of_contents: true
---
@@ -9,67 +9,65 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
<div className="strategy-content">
**TO-BE · Target operating model — not installed controls or company results.**
## Two stages toward Target
## What must be true before widening the rollout?
<ArchifyDiagram name="strategy-roadmap" title="Adopt skills → Future Autonomous Agent" story />
Advance by exit evidence, not promised dates or usage volume. Each stage can hold, narrow or stop; changed client, data or authority boundaries reopen earlier gates.
**Humans direct, guide and review throughout.** Stage 1 standardizes skills in human + AI Agent work across the SDLC. Proven skills, measurements and working practices become the foundation for Stage 2: the future Autonomous Agent in [Target](./target-operating-model.mdx).
<ArchifyDiagram name="strategy-roadmap" title="Foundation, pilot, reliable distribution, coordination and departmental expansion have exit gates" story />
Target operating model—not deployed autonomy, an agreed schedule or approved KPI thresholds.
- **Start bounded:** named people, lawful data handling and a reproducible baseline precede the pilot.
- **Prove recovery before coordination:** verified versions, revocation and human takeover are prerequisites.
- **Expand by department:** accepted outcomes, guardrails, total cost and experience justify continuation; sensitive decisions remain human.
## Stage 1: Delivery first
<ArchifyDiagram name="strategy-roadmap-adoption" title="Delivery first → Other SDLC phases, order undecided" story />
Start with Delivery, then extend skills adoption to the remaining SDLC phases. Their order is not yet decided. **Delivery keeps improving as adoption expands.**
## Improve within each phase
<ArchifyDiagram name="strategy-roadmap-loop" title="Each phase: understand → baseline → topology → use → collect → reassess → repeat" story />
Repeat this loop within every phase—not as six global roadmap stages. Skills topology defines **what skills exist, how they relate, when they are used and how they work together**, including handoffs—not just a catalogue.
## Delivery in practice
**Understand the engineering path first:** codebase structure and existing principles → system-logic source → tests → builds and packaging → deployments. Inspect actual practices, tooling, controls and problems with the people doing the work, rather than assuming the documented process is the real one.
**Establish the comparison, then engineer skills.** Define metrics/KPIs and a baseline for comparable work before changing it. [Skills Measurement](./measurement/index.mdx) explains collection and calculation. Connect reviewed skills to the engineering path, with clear triggers, dependencies and acceptance checks.
**Use, collect, compare, repeat.** A human works with an AI Agent on real changes. Collect results, friction and feedback alongside quality, cost and verification effort. Compare with the baseline to understand the new current situation; revise the skills and working practices, then run the loop again.
<details>
<summary>Stage-by-stage entry evidence, work, exit gates and hold conditions</summary>
<summary>Supporting gate evidence and hold conditions</summary>
**TO-BE · Target operating model.** Introduction depends on the [roadmap gates](./roadmap.mdx); these pages do not describe installed controls or measured company results.
These are recommended implementation gates, not assigned human owners, approved thresholds or installed integrations. Agree acceptance criteria for each selected workflow before evaluating it.
### Foundation
### Understand the current situation
**Entry evidence** — Strategy scope accepted for planning; existing teams identified.
Sample representative repositories and changes. Retain repository revisions, tests and CI reliability, maintainability, technical debt and security findings. Trace ownership, review and release practices, handoffs, rework and bottlenecks. Keep baseline findings, a process map and prioritized gaps; hold selection if the sample cannot explain how work is delivered and accepted.
**Work** — Inventory actual client hosts/builds, provider/data terms, repositories, authority, owners and event availability; select low-risk workflows and metric definitions.
### Prepare safe, measurable human + AI work
**Exit evidence and hold condition** — Named accountable people and independent reviewers, bounded pilot charter, forbidden actions, data/retention decision and reproducible baseline plan. Hold if accountability or lawful collection is unresolved.
Inventory actual client hosts/builds, provider/data terms, authority and event availability. Confirm accountable people and independent reviewers, forbidden actions, data/retention decisions, recovery and a reproducible baseline. Hold if accountability, lawful collection or critical acceptance checks remain unresolved.
### Governed skills pilot
Close critical gaps such as exposed secrets, unclear approval authority or unreliable acceptance checks. Broader refactoring and non-critical debt can run alongside the selected work. Stage 1 introduces no new privileged autonomous actions.
**Entry evidence** — Foundation evidence approved; no privileged autonomous effects.
### Engineer and evaluate connected skills
**Work** — Build a small registry, immutable contract, client adapters, evaluations, coaching and synthetic measurement verification.
Use a small registry, immutable skill contracts, qualified client adapters, evaluations and coaching. Verify the measurement calculations with synthetic fixtures before interpreting real outcomes. Require mandatory safety checks, independent task acceptance, reconciled source coverage and user feedback. Hold or narrow scope if quality or coverage is inadequate; usage alone does not justify expansion.
**Exit evidence and hold condition** — Qualified client/skill tuples, mandatory safety checks, independent task acceptance, reconciled coverage and user feedback. Hold or narrow scope if quality or data coverage is inadequate.
### Extend adoption without stopping improvement
### Reliable distribution
Prove canary updates, effective-version readback, version locking, exception expiry, stale/offline handling, rollback and revocation. Hold if effective versions or controls cannot be verified or the catalog cannot be supported.
**Entry evidence** — Pilot quality and usefulness support continuing.
Use evidence to choose the next SDLC phase; no second or third phase is assigned here. Continue the improvement loop in Delivery and every phase already using skills.
**Work** — Canary updates, effective-version readback, version locking, exception expiry, stale/offline handling and rollback.
### Prepare for the future Autonomous Agent
**Exit evidence and hold condition** — Tested revocation and recovery, no bypass of central privileged gates, owners can support the catalog. Hold if effective versions or controls cannot be verified.
### Logical SDLC coordination
**Entry evidence** — Distribution, authority and measurement evidence stable.
**Work** — Observe and assemble evidence first, then propose and route work within scoped identities and budgets.
**Exit evidence and hold condition** — Exact-artifact approvals, idempotency, duplicate/outage recovery, separation of duties, audit and kill-switch drills pass; humans can take over. No authority expansion based on usage alone.
### Departmental expansion
**Entry evidence** — Each department supplies a workflow owner, outcome, data boundary and capacity.
**Work** — Add Operations, Marketing, Finance & Accounting and HR & Administration workflows with domain-specific review; Product and Technology continue quality improvement.
**Exit evidence and hold condition** — Departmental accepted outcomes, guardrails, total cost and experience justify continuation; sensitive decisions stay human. Stop or roll back workflows without adequate evidence.
There are no invented launch dates, budgets, staffing commitments or guaranteed gains. Phase gates permit narrowing or stopping. Re-evaluate earlier phases when the underlying client, provider, data scope or authority changes.
Stage 2 builds on proven skills, measurements and working practices—not permission inferred from adoption alone. Before granting scoped execution authority, prove observation and evidence assembly, then proposing and routing work. Recommended controls include exact-artifact approvals, idempotency, duplicate/outage recovery, separation of duties, audit and kill-switch drills. Prove human takeover; never infer permission from missing evidence. The agent ultimately executes and governs the cycle, not only routes tasks, while humans retain direction and review. Keep sensitive decisions human. Changed client, provider, data or authority boundaries reopen the relevant checks.
</details>
**Next:** [Return to the strategy destination →](./index.mdx)
**Next:** [Stage - 01 - Skills Adoption →](./stage-01-skills-adoption.mdx)
</div>
+34 -2
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@@ -13,7 +13,7 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
## When should a pilot become a team workflow?
Expand only when a bounded canary produces independently accepted work and useful feedback. Teach people to verify artifacts and recover without AI, not merely invoke a skill.
Expand only when a bounded canary produces independently accepted work and useful feedback. Teach people to verify artifacts and recover without AI, not merely invoke a skill. Compare **Workflow effectiveness** with the current-workflow baseline; observe **Skills effectiveness & health** separately as skills enter use. More adoption does not prove improved work, and before/after trends alone are not causal evidence.
<ArchifyDiagram name="strategy-adoption" title="Choose a workflow, coach a canary, verify outcomes and improve before expansion" story />
@@ -36,6 +36,38 @@ No developer rankings, individual productivity scores, minimum invocation quotas
</details>
**Next:** [Measure accepted outcomes, not activity →](./measurement.mdx)
<details>
<summary>Pilot evidence, illustrative report and expansion</summary>
## Apply the selected measures in the pilot
Use the relevant subset agreed in [Baseline](./baseline.mdx), not every entry in the [Measurement registry](./measurement/index.mdx). Keep its eligibility, independent acceptance and follow-up rules. Capture inputs as work happens; record exact skill revision and client configuration, leaving missing versions unknown. Do not reconstruct review effort from elapsed PR time.
The following questions are candidates, not a mandatory pilot bundle. Proposed owners and cadences need agreement before collection:
| If this question is selected | Evidence and pilot review |
| --- | --- |
| Are tasks reaching acceptance? | Join tracker starts to independent acceptance, failure and abandonment. Apply [validated task success](./measurement/validated-task-success.mdx) to matured starts; retain failed, abandoned and unresolved tasks in the denominator and show unknown outcomes and coverage. Proposed weekly reviewer: Quality Engineering. |
| Is quality holding up? | Link accepted changes to confirmed defects, severity and follow-up dates; retain PR/CI evidence. Apply [escaped quality](./measurement/changes-with-escaped-quality-issues.mdx) after follow-up, counting each affected change once, alongside severe incidents. Missing links are not clean work. Proposed monthly reviewer: Quality Engineering. |
| What does an accepted outcome cost? | Reconcile invoices and usage, sampled review/rework minutes at approved rates, unsuccessful attempts and allocated licenses/tooling. Apply [cost per accepted outcome](./measurement/cost-per-accepted-outcome.mdx) to the same matured start cohort; distinguish effort from waiting. Missing buckets make the estimate partial. Proposed monthly reviewer: Finance & Accounting; restate late invoices. |
| Can people confidently verify the work? | Use the anonymous 1–5 survey for confidence, manageable workload and usefulness as separate items. Report the [confidence measure](./measurement/verification-confidence-and-cognitive-load.mdx), distribution and response rate; protect small groups. Proposed reviewer after each pilot cycle: People & Administration. This is enablement evidence, not proven saved time. |
### What a pilot report looks like
**Illustrative arithmetic, not company results or targets.** The bundled synthetic fixture shows four matured starts: one accepted, one failed, one abandoned and one unresolved. Confirmed success is **1 / 4 × 100 = 25%**, with **75%** known-outcome coverage. A newer start has not finished its observation period and is shown separately.
Recorded compute spend is **EUR 60 / 1 = EUR 60** per accepted outcome—a **partial estimate** because licenses, tooling, review and rework are missing. Five survey responses total 20 points: **20 / 5 = 4** out of 5; response rate is **5 / 10 × 100 = 50%**. Reconcile the unknown task and missing costs instead of claiming a skills benefit. Reproduce it with `node scripts/ai-kpi.mjs`; [fixture and limits](./measurement/synthetic-example.mdx).
### Revisit selection as adoption expands
Selection precision/recall qualify named skill versions against labeled cases; they do not measure real-workflow acceptance. Keep any skill/version evaluation separate from the live task-success cohort. Skill-specific measures with no applicable population are N/A, not zero; missing evidence for an existing population remains unknown.
Keep relevant outcome evidence comparable; add reach measures only if they answer the expanded workflow's questions. For [supported bundle coverage](./measurement/supported-bundle-coverage.mdx), freeze the expected active installation inventory and compare observed bundle/adapter revisions to support and revocation records. Offline or stale entries stay in the denominator. Platform & IT is the proposed weekly and at-revocation reviewer.
For [approved-workflow adoption](./measurement/approved-workflow-adoption.mdx), freeze the lawfully enrolled participant cohort and distinguish qualified-adapter observations from labeled declarations. Report the observed lower bound with source coverage: missing use is unknown; installation and loading are not use. Data & AI is the proposed monthly reviewer. No invocation quotas or employee rankings. Return to Baseline for a new workflow rather than treating rollout as company-wide metric collection.
</details>
**Next:** [Maintain skills using the agreed evidence →](./skills-maintenance.mdx)
</div>
+17 -2
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@@ -13,7 +13,7 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
## What happens when a skill drifts or causes harm?
Monitor usefulness and safety throughout a revision's life. Unsafe behavior triggers containment; a correction returns through independent tests and approval, never automatic reinstatement.
Monitor both **Workflow effectiveness** (comparable outcomes, safety, cost and human experience) and **Skills effectiveness & health** (selection, supported use and substantive review) throughout a revision's life. Use the evidence to improve, retain or retire skills; adoption or current review dates alone do not prove better work. Unsafe behavior triggers containment; a correction returns through independent tests and approval, never automatic reinstatement.
<ArchifyDiagram name="strategy-maintenance" title="Monitor, triage and test corrections; promote safely or contain and roll back" story />
@@ -44,6 +44,21 @@ Owner ratification is required before adoption. Review earlier after incidents o
</details>
**Next:** [Use exit evidence to choose the next rollout stage →](./roadmap.mdx)
<details>
<summary>Ongoing reporting and comparison</summary>
## Keep selected evidence useful
Continue the measures agreed for the workflow in [Baseline](./baseline.mdx) and applied during [Adoption](./skills-adoption.mdx). Revisit relevance when scope changes; the [registry](./measurement/index.mdx) is a source of choices, not a requirement to collect every metric. Preserve current-workflow comparisons separately from named skill/version evaluations. No applicable skill population is N/A, not zero; missing evidence for existing revisions is unknown and must not improve reported health.
If substantive-review coverage is selected, join each active approved catalog revision to its owner, substantive review evidence and due date. Apply [review coverage](./measurement/skills-within-substantive-review-window.mdx): revisions with all three current / all active approved revisions × 100. The proposed Data & AI review is monthly and at each release, subject to agreement. Report overdue/ownerless revisions and deprecated or revoked versions still in use—not just a percentage.
At each agreed report, compare like workflows with their recorded starting position. Publish period, counts, exclusions, source coverage and changes in calculation or scope. Zero denominators mean “not available”; unresolved gaps remain visible. Trends are descriptive, not causal ROI. Reconcile late evidence using versioned corrections and distinguish changed practice from changed measurement.
Act on critical policy effects immediately; do not wait for a reporting cycle. Use selection precision/recall at qualification, or service-level delivery and departmental outcome measures, only where relevant and their source links are feasible. Confirm purpose, lawful basis, access and retention before changing collection, following the [shared safeguards](./measurement/collection-and-safeguards.mdx).
</details>
**Next:** [Stage - 02 - Autonomous Agent →](./stage-02-autonomous-agent.mdx)
</div>
@@ -0,0 +1,41 @@
---
id: stage-01-skills-adoption
title: Stage - 01 - Skills Adoption
description: Build proven skills and measurable working practices through human and AI Agent collaboration, starting with Delivery.
hide_table_of_contents: true
---
<div className="strategy-content">
**Human + AI Agent → proven skills and working practices → future Autonomous Agent.**
This first stage of the [Roadmap](./roadmap.mdx) standardizes skills in real human + AI Agent work. It builds the foundation for [Target](./target-operating-model.mdx), while people direct the work, verify outcomes and improve the skills.
## Delivery first
Start with the engineering path: codebase structure and existing principles → system-logic source → tests → builds and packaging → deployments. Understand actual practices, tooling, controls and problems before changing them.
Adoption then extends to other SDLC phases; their order is not yet decided. Delivery keeps improving as adoption expands.
## Repeat within each phase
**Understand the current situation → select relevant KPIs and establish a workflow baseline → engineer skills topology → use skills in real work → collect agreed metrics and feedback → understand the new current situation → repeat.**
Skills topology connects what skills exist, how they relate, when they are used and how they work together. Compare accepted outcomes, quality, cost and review effort with the baseline; use friction and feedback to revise the skills and working practices. These are repeating steps within each phase, not additional roadmap stages.
## Put the foundation into practice
- [Measurement](./measurement/index.mdx) — distinguish Workflow effectiveness from Skills effectiveness & health; candidate inclusion does not require collection or baselining.
- [Baseline](./baseline.mdx) — understand current workflow outcomes first, select relevant metrics and record feasible starting evidence or explicit gaps; absent skills are not zero performance.
- [Governance](./skills-governance.mdx) — define ownership, authority and approval of skills.
- [Quality](./skills-quality.mdx) — qualify skills and verify their outcomes before wider use.
- [Adoption](./skills-adoption.mdx) — compare workflow outcomes and observe skill use separately, with a supported client and a manual path.
- [Maintenance](./skills-maintenance.mdx) — monitor both tracks to improve or retire skills, control versions and recover from unsafe updates.
Proven skills, measurements and working practices support [Stage - 02 - Autonomous Agent](./stage-02-autonomous-agent.mdx); adoption alone does not grant autonomous execution authority.
These six topics belong to Stage 01, not six additional roadmap stages. Establish a baseline per workflow as adoption reaches it—not a mandatory company-wide baseline of every registry metric.
**Next:** [Browse the Measurement registry →](./measurement/index.mdx)
</div>
@@ -0,0 +1,24 @@
---
id: stage-02-autonomous-agent
title: Stage - 02 - Autonomous Agent
description: Introduce the future Autonomous Agent on proven skills and measured practices while humans retain direction and review.
hide_table_of_contents: true
---
<div className="strategy-content">
**Proven skills and measured practices → future Autonomous Agent → human-directed SDLC.**
This future stage of the [Roadmap](./roadmap.mdx) builds on [Stage - 01 - Skills Adoption](./stage-01-skills-adoption.mdx). The destination is [Target](./target-operating-model.mdx): an Autonomous Agent that executes and governs the SDLC cycle, with humans retaining direction and review.
## Build on what has been proven
Carry forward proven skills, measurements and working practices from real human + AI Agent work. The skills foundation provides [governance](./skills-governance.mdx), [quality checks](./skills-quality.mdx), [adoption feedback](./skills-adoption.mdx), [measurement](./measurement/index.mdx) and [maintenance](./skills-maintenance.mdx); it is not permission to expand authority automatically.
## Introduce authority deliberately
Establish reliable observation and evidence assembly, then proposing and routing work, before granting scoped execution authority. The Roadmap describes recommended controls and hold conditions, including exact-artifact approvals, independent review, recovery and human takeover. Sensitive decisions remain human; missing evidence never means permission.
This is future direction, not deployed autonomy, agreed delivery dates or approved KPI thresholds. The transition depends on reviewed evidence and explicit authority decisions, not adoption volume alone.
</div>
+49 -20
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@@ -1,7 +1,8 @@
---
id: target-operating-model
title: Target operating model
description: One logical coordinator; local client choice; independent authority; all departments.
sidebar_label: Target
description: An autonomous agent executes and governs the SDLC; humans direct, guide and review the repeating cycle.
hide_table_of_contents: true
---
@@ -9,42 +10,44 @@ import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
<div className="strategy-content">
**TO-BE · Target operating model — not installed controls or company results.**
**TO-BE · Target operating model — the intended strategy, not a deployed system.**
## Who coordinates, and who can authorize delivery?
## Autonomous SDLC, human direction
One logical coordinator routes work; people retain authority. Local agents propose changes, while independent CI and human approval govern what the release service can execute.
<ArchifyDiagram name="strategy-target" title="Autonomous agent executes and governs the SDLC; humans direct, guide and review" story />
<ArchifyDiagram name="strategy-target" title="People authorize; skills guide; independent gates protect release" story />
An autonomous agent executes and governs every phase. Humans direct, guide and review it; a separate human-controlled AI Agent contributes to each phase from outside the cycle.
- **Local choice:** Copilot, Claude Code and Cline use qualified adapters and pinned skills.
- **Central controls:** neither laptops nor the coordinator hold production credentials.
- **Existing organization:** six departments, eleven teams; Data &amp; AI owns coordination, not their decisions.
**Solid arrows:** lifecycle · **Dotted spokes:** execution and governance · **Dashed arrows:** contributions.
**Scope → Architecture → UI/UX → Planning → Delivery → UAT → Security → Releases → Scope**
Each stage follows the previous one. Releases returns to Scope; the cycle repeats indefinitely, with human direction informing the next iteration.
<details>
<summary>Trust boundaries, recovery and detailed delivery path</summary>
<summary>Supporting implementation options: trust boundaries and recovery</summary>
## Coordination without transferred authority
## Controls that support autonomous execution
The diagram is an overview; the equivalent delivery path below remains readable on narrow screens. Expand the diagram to inspect its trust boundaries and use its zoom controls for individual relationships.
The lifecycle above is the strategic direction. The earlier control design below is a supporting implementation option, not an agreed assignment of approval roles or a claim of installed controls. Detailed approval policy and responsibilities remain to be defined with humans.
1. Accountable people authorize the work scope; one logical coordinator routes tasks.
1. Humans direct, guide and review; the autonomous agent executes and governs work across the lifecycle.
2. The reviewed registry supplies pinned skills and qualified adapters to coordinator and local clients.
3. Laptop contributors propose changes; independent repository and CI checks verify the exact revision.
4. A human approves that artifact; only the release service holds production credentials.
5. Restricted audit and measurement evidence returns to people and informs the next authorized task.
3. Laptop contributors can participate alongside the agent; independent repository and CI checks verify the exact revision.
4. A separate release service and artifact-scoped approval are possible controls, subject to the policy humans define.
5. Restricted audit and measurement evidence supports human review and the next Scope iteration.
<ArchifyDiagram name="ai-adoption-target" title="TO-BE AI adoption: human accountability, no direct production authority for laptops or coordinator" />
<ArchifyDiagram name="ai-adoption-target" title="Supporting control option, not agreed approval policy: isolated release authority" />
**TO-BE · Target operating model.** Introduction depends on the [roadmap gates](./roadmap.mdx); these pages do not describe installed controls or measured company results.
### One coordination function, distributed contributions
Data & AI owns the coordinating function, with the existing AI Architect function connecting it to Technology leadership. The logical coordinator maintains approved work records, dependencies, evidence requests, bounded retries and escalation. It can summarize, propose work and route decisions. It cannot declare its own work approved, change protected checks, authorize production release or replace the responsible human.
The autonomous agent is more than a task router: it executes and governs the repeating SDLC under human direction, guidance and review. A coordinating function maintains work records, dependencies, evidence requests, bounded retries and escalation. Data & AI and the existing AI Architect function are possible implementation contributors, not newly assigned approval authorities. Autonomous execution does not remove human involvement or allow the agent to redefine its own controls.
One logical coordinator does not mean one fragile process. A durable task ledger, explicit state transitions, leases and idempotency keys allow recovery or multiple replicas without duplicate delivery. Inference outages stop new agent decisions, not the organization's ability to take over. People can resume work through the normal deterministic workflow. Evidence and authorization services fail closed for privileged actions; missing evidence never becomes permission.
The delivery path is: an approved problem and acceptance criteria; an authorized task; local or isolated worker proposals; independently reviewed repository changes; exact-revision CI evidence; a human release decision; execution by the release service; then operational feedback. Product Management accepts the outcome hypothesis and business result. Product Design reviews experience and accessibility. Product Engineering owns the code and maintainability. Quality Engineering assesses quality independently. Architecture & Security assesses risk. Platform & IT operates the delivery boundary. No arrow from a laptop or coordinator goes directly to production authority.
These controls support the sequence Scope → Architecture → UI/UX → Planning → Delivery → UAT → Security → Releases → Scope; they do not replace it with a separate lifecycle. Product, engineering, design, quality, security and platform expertise inform human direction and review. Specific approval assignments and release permissions are implementation decisions still to be defined.
### Trust and authority boundaries
@@ -57,10 +60,12 @@ Central controls verify protected-branch review, actual artifact identity, exact
</details>
<details>
<summary>Responsibilities and first workflows for all eleven teams</summary>
<summary>Candidate contributions and first workflows for all eleven teams</summary>
### Department contributions
The existing team structure provides a starting point. The contributions below are implementation proposals, not settled approval roles or lifecycle gates.
### Product / Product Management
**Contribution and retained human decision** — Own pilot priorities, acceptance criteria and outcome hypotheses; decide product value.
@@ -133,6 +138,30 @@ See the existing [organization structure](/organization/structure/), [department
</details>
**Next:** [Decide who owns and approves each skill →](./skills-governance.mdx)
<details>
<summary>Strategy rationale and reading map</summary>
### Govern skills first, expand authority only with evidence
Eldorado's target is to make AI-assisted work dependable across the organization: useful guidance, clear human ownership, controlled execution and measurable outcomes. The first investment is a governed skills system, not an autonomous replacement for the organization. A skill packages reusable working knowledge, prerequisites and verification steps. It helps an agent perform a task; it does not grant permission or guarantee that the work is correct.
The target combines an autonomous agent executing and governing the SDLC with humans directing, guiding and reviewing it. Developer choice on local laptops remains a supporting option: Copilot, Claude Code and Cline can receive reviewed portable skill content through qualified adapters. Repository, CI and release controls support execution; detailed approval policies remain implementation decisions, not new roles established by this strategy.
The strategy describes the intended operating model and the evidence required to introduce it. It does not establish that these controls are installed, that every client is supported, or that AI has improved Eldorado's performance. The current reference is the documented six-department organization. Rollout begins by validating actual clients, responsibilities, data boundaries and available evidence.
Success means accepted outcomes with maintained quality, controlled risk and understood total cost. Faster activity without reliable outcomes is not success. More skill invocations, generated lines or tool subscriptions are not productivity targets. People remain accountable for product, customer, financial and personnel decisions.
### Navigate the strategy
- [Roadmap](./roadmap.mdx) — Evidence-gated phases, no promised dates or budgets.
- [Skills governance](./skills-governance.mdx) — Contract, lifecycle, decision rights, adapters, locking, exceptions.
- [Skills quality](./skills-quality.mdx) — Risk tiers, independent evaluation, repeated trials, adversarial conformance.
- [Skills adoption](./skills-adoption.mdx) — Workflow-led coaching, client choice, feedback, manual path.
- [Measurement](./measurement/index.mdx) — Full KPI contracts, minimal events, illustrative calculations, privacy and limits.
- [Skills maintenance](./skills-maintenance.mdx) — Review, drift, deprecation, rollback and incident handling.
</details>
**Next:** [Follow the Roadmap toward Target →](./roadmap.mdx)
</div>
+1
View File
@@ -18,6 +18,7 @@ const config: Config = {
theme: {customCss: './src/css/custom.css'},
} satisfies Preset.Options]],
plugins: [
['@docusaurus/plugin-client-redirects', {redirects: [{from: '/strategy/', to: '/strategy/target-operating-model/'}]}],
['@docusaurus/plugin-content-docs', {id: 'organization', path: 'docs/organization', routeBasePath: 'organization', sidebarPath: './sidebars/organization.ts'}],
['@docusaurus/plugin-content-docs', {id: 'strategy', path: 'docs/strategy', routeBasePath: 'strategy', sidebarPath: './sidebars/strategy.ts'}],
['@docusaurus/plugin-content-docs', {id: 'contribution', path: 'docs/contribution', routeBasePath: 'contribution', sidebarPath: './sidebars/contribution.ts'}],
+2 -1
View File
@@ -15,11 +15,12 @@
"verify:build": "node scripts/verify.mjs --build",
"diagrams:build": "node scripts/build-diagrams.mjs",
"test": "node --test scripts/*.test.mjs",
"test:browser": "node scripts/browser/strategy-story.cjs && node scripts/browser/inline-controls.cjs",
"test:browser": "node scripts/browser/measurement-pages.cjs && node scripts/browser/sidebar-coverage.cjs && node scripts/browser/skills-stories.cjs && node scripts/browser/strategy-navigation.cjs && node scripts/browser/strategy-story.cjs && node scripts/browser/inline-controls.cjs && node scripts/browser/sdlc-cycle.cjs && node scripts/browser/target-midpoints.cjs && node scripts/browser/skills-measurement.cjs && node scripts/browser/roadmap.cjs && node scripts/browser/roadmap-timeline.cjs",
"kpi:example": "node scripts/ai-kpi.mjs"
},
"dependencies": {
"@docusaurus/core": "3.10.2",
"@docusaurus/plugin-client-redirects": "3.10.2",
"@docusaurus/preset-classic": "3.10.2",
"@docusaurus/theme-common": "3.10.2",
"@easyops-cn/docusaurus-search-local": "0.55.3",
+51
View File
@@ -14,6 +14,9 @@ importers:
'@docusaurus/core':
specifier: 3.10.2
version: 3.10.2(@mdx-js/react@3.1.1(@types/react@19.1.13)(react@19.1.1))(debug@4.4.3)(postcss@8.5.28)(react-dom@19.1.1(react@19.1.1))(react@19.1.1)(typescript@5.9.3)
'@docusaurus/plugin-client-redirects':
specifier: 3.10.2
version: 3.10.2(@mdx-js/react@3.1.1(@types/react@19.1.13)(react@19.1.1))(postcss@8.5.28)(react-dom@19.1.1(react@19.1.1))(react@19.1.1)(typescript@5.9.3)
'@docusaurus/preset-classic':
specifier: 3.10.2
version: 3.10.2(@algolia/client-search@5.59.0)(@mdx-js/react@3.1.1(@types/react@19.1.13)(react@19.1.1))(@types/react@19.1.13)(postcss@8.5.28)(react-dom@19.1.1(react@19.1.1))(react@19.1.1)(search-insights@2.17.3)(typescript@5.9.3)
@@ -1115,6 +1118,13 @@ packages:
react: '*'
react-dom: '*'
'@docusaurus/plugin-client-redirects@3.10.2':
resolution: {integrity: sha512-z5I5ttCXw+8y2gHVZvqAMmUw4Rb0ZzKA5eCPk87SfM/jCKOTvE24yDpPAwwipvug96ij7mOwEHXWw8G4LlWdGA==}
engines: {node: '>=20.0'}
peerDependencies:
react: ^18.0.0 || ^19.0.0
react-dom: ^18.0.0 || ^19.0.0
'@docusaurus/plugin-content-blog@3.10.2':
resolution: {integrity: sha512-0cbEnNKf0InmLkhj/+nVRmqEnWEoOE8Mh+2x1qOXI0qYpCnphq4RXknVJ8BvybKRXqYVvbmdMfiJSup+k4tm5w==}
engines: {node: '>=20.0'}
@@ -6784,6 +6794,47 @@ snapshots:
- uglify-js
- webpack-cli
'@docusaurus/plugin-client-redirects@3.10.2(@mdx-js/react@3.1.1(@types/react@19.1.13)(react@19.1.1))(postcss@8.5.28)(react-dom@19.1.1(react@19.1.1))(react@19.1.1)(typescript@5.9.3)':
dependencies:
'@docusaurus/core': 3.10.2(@mdx-js/react@3.1.1(@types/react@19.1.13)(react@19.1.1))(debug@4.4.3)(postcss@8.5.28)(react-dom@19.1.1(react@19.1.1))(react@19.1.1)(typescript@5.9.3)
'@docusaurus/logger': 3.10.2
'@docusaurus/utils': 3.10.2(clean-css@5.3.3)(cssnano@6.1.2(postcss@8.5.28))(html-minifier-terser@7.2.0)(postcss@8.5.28)(react-dom@19.1.1(react@19.1.1))(react@19.1.1)
'@docusaurus/utils-common': 3.10.2(clean-css@5.3.3)(cssnano@6.1.2(postcss@8.5.28))(html-minifier-terser@7.2.0)(postcss@8.5.28)(react-dom@19.1.1(react@19.1.1))(react@19.1.1)
'@docusaurus/utils-validation': 3.10.2(postcss@8.5.28)(react-dom@19.1.1(react@19.1.1))(react@19.1.1)
eta: 2.2.0
fs-extra: 11.4.1
lodash: 4.18.1
react: 19.1.1
react-dom: 19.1.1(react@19.1.1)
tslib: 2.8.1
transitivePeerDependencies:
- '@docusaurus/faster'
- '@mdx-js/react'
- '@minify-html/node'
- '@napi-rs/image'
- '@parcel/css'
- '@rspack/core'
- '@swc/core'
- '@swc/css'
- '@swc/html'
- bufferutil
- clean-css
- cssnano
- csso
- debug
- esbuild
- html-minifier-terser
- imagemin
- lightningcss
- postcss
- sharp
- supports-color
- svgo
- typescript
- uglify-js
- utf-8-validate
- webpack-cli
'@docusaurus/plugin-content-blog@3.10.2(@docusaurus/plugin-content-docs@3.10.2(@mdx-js/react@3.1.1(@types/react@19.1.13)(react@19.1.1))(postcss@8.5.28)(react-dom@19.1.1(react@19.1.1))(react@19.1.1)(typescript@5.9.3))(@mdx-js/react@3.1.1(@types/react@19.1.13)(react@19.1.1))(postcss@8.5.28)(react-dom@19.1.1(react@19.1.1))(react@19.1.1)(typescript@5.9.3)':
dependencies:
'@docusaurus/core': 3.10.2(@mdx-js/react@3.1.1(@types/react@19.1.13)(react@19.1.1))(debug@4.4.3)(postcss@8.5.28)(react-dom@19.1.1(react@19.1.1))(react@19.1.1)(typescript@5.9.3)
@@ -0,0 +1,162 @@
{
"sourceCommit": "b9c2047c614dd4e825fa746815104d35d9500739",
"sourcePath": "docs/strategy/reference/measurement-contracts.mdx",
"metrics": [
{
"oldAnchor": "validated-task-success",
"title": "Validated task success",
"docId": "measurement/validated-task-success",
"url": "/strategy/measurement/validated-task-success/",
"calculationId": "validated-task-success",
"status": "prototype",
"contractSha256": "925100f4c84f43e2cfdca4a89d6b4a984c808dae2d2ec5e57202318f70b9c544"
},
{
"oldAnchor": "skill-selection-precision",
"title": "Skill selection precision",
"docId": "measurement/skill-selection-precision",
"url": "/strategy/measurement/skill-selection-precision/",
"calculationId": "selection-precision",
"status": "prototype",
"contractSha256": "189e93e4e5f52a7e70e2045c6b824a9da621382f39ba8ce9a59c0c04812f0ce3"
},
{
"oldAnchor": "skill-selection-recall",
"title": "Skill selection recall",
"docId": "measurement/skill-selection-recall",
"url": "/strategy/measurement/skill-selection-recall/",
"calculationId": "selection-recall",
"status": "prototype",
"contractSha256": "847b5ba6094585eb88b8eb2b55b42e0f3c6822dcaa1629256ad0501a13eb7f18"
},
{
"oldAnchor": "supported-bundle-coverage",
"title": "Supported bundle coverage",
"docId": "measurement/supported-bundle-coverage",
"url": "/strategy/measurement/supported-bundle-coverage/",
"calculationId": "supported-bundle-coverage",
"status": "unimplemented",
"contractSha256": "8b4dc2dbdfb6999fac283814f518645d0830d515125910d79dd7dc8763f0521c"
},
{
"oldAnchor": "approved-workflow-adoption",
"title": "Approved-workflow adoption",
"docId": "measurement/approved-workflow-adoption",
"url": "/strategy/measurement/approved-workflow-adoption/",
"calculationId": "useful-adoption",
"status": "unimplemented",
"contractSha256": "355996d5adb603021ba22f9e1f7f08f2fbea017dac9ee0a4bd42cc00bf7adea3"
},
{
"oldAnchor": "change-lead-time",
"title": "Change lead time",
"docId": "measurement/change-lead-time",
"url": "/strategy/measurement/change-lead-time/",
"calculationId": "change-lead-time",
"status": "unimplemented",
"contractSha256": "96fd0edd5eba139a7c5905b606bcc96e608c5294acd2ef0c962fdb7d339d8251"
},
{
"oldAnchor": "deployment-frequency",
"title": "Deployment frequency",
"docId": "measurement/deployment-frequency",
"url": "/strategy/measurement/deployment-frequency/",
"calculationId": "deployment-frequency",
"status": "unimplemented",
"contractSha256": "5a34ba52e5c2768e29a1a7574274e07a65509f75063e89ccc7ce1b035aeff4c5"
},
{
"oldAnchor": "change-fail-rate",
"title": "Change fail rate",
"docId": "measurement/change-fail-rate",
"url": "/strategy/measurement/change-fail-rate/",
"calculationId": "change-fail-rate",
"status": "prototype",
"contractSha256": "d2a4ecaddd468f42db5824f9bfab8a8c8fcdf9157b33b4e4f047269a83c8567b"
},
{
"oldAnchor": "failed-deployment-recovery-time",
"title": "Failed deployment recovery time",
"docId": "measurement/failed-deployment-recovery-time",
"url": "/strategy/measurement/failed-deployment-recovery-time/",
"calculationId": "failed-deployment-recovery-time",
"status": "unimplemented",
"contractSha256": "489fd756883d4ccee1769fcfaa0b67725420463df2b1f6faf3e7faa7002f7a80"
},
{
"oldAnchor": "deployment-rework-rate",
"title": "Deployment rework rate",
"docId": "measurement/deployment-rework-rate",
"url": "/strategy/measurement/deployment-rework-rate/",
"calculationId": "deployment-rework-rate",
"status": "prototype",
"contractSha256": "e8ade457136feac3ad39e9eba2a9d67142bc605727d9f4f038a7df6d5a0707fd"
},
{
"oldAnchor": "changes-with-escaped-quality-issues",
"title": "Changes with escaped quality issues",
"docId": "measurement/changes-with-escaped-quality-issues",
"url": "/strategy/measurement/changes-with-escaped-quality-issues/",
"calculationId": "escaped-quality-rate",
"status": "prototype",
"contractSha256": "c436d504c8b3a9f655de18b2ca00fa8a0ab47ea1cf37637ff21561f81ecc77c9"
},
{
"oldAnchor": "confirmed-policy-effects",
"title": "Confirmed policy effects",
"docId": "measurement/confirmed-policy-effects",
"url": "/strategy/measurement/confirmed-policy-effects/",
"calculationId": "policy-effects",
"status": "prototype",
"contractSha256": "b64c02f5516b08421fa8b816f0f490571afd05baf5ad6e9d92cb6a7b711ac82a"
},
{
"oldAnchor": "cost-per-accepted-outcome",
"title": "Cost per accepted outcome",
"docId": "measurement/cost-per-accepted-outcome",
"url": "/strategy/measurement/cost-per-accepted-outcome/",
"calculationId": "cost-per-accepted-outcome",
"status": "prototype",
"contractSha256": "d8865ec31315d3c8398ec58cdb6665cb506a7d6309ebec3da0ca7dea84a5f406"
},
{
"oldAnchor": "verification-confidence-and-cognitive-load",
"title": "Verification confidence and cognitive load",
"docId": "measurement/verification-confidence-and-cognitive-load",
"url": "/strategy/measurement/verification-confidence-and-cognitive-load/",
"calculationId": "human-experience",
"status": "prototype",
"contractSha256": "01e017471004c5f780fd0c2671a4d4449d392956cb4c5f0bd7791959d6a9af9a"
},
{
"oldAnchor": "skills-within-substantive-review-window",
"title": "Skills within substantive review window",
"docId": "measurement/skills-within-substantive-review-window",
"url": "/strategy/measurement/skills-within-substantive-review-window/",
"calculationId": "maintenance-health",
"status": "unimplemented",
"contractSha256": "339fe0da6b382a34c52b5ec6005ce08a7293a2b07ccd88540a6df03a02d96ad4"
},
{
"oldAnchor": "workflow-specific-business-acceptance",
"title": "Workflow-specific business acceptance",
"docId": "measurement/workflow-specific-business-acceptance",
"url": "/strategy/measurement/workflow-specific-business-acceptance/",
"calculationId": "department-outcome",
"status": "unimplemented",
"contractSha256": "55fce8843409a1bc1383fef3cee5b9a616b44fa8d45ba84c6e4ed490a25f2de4"
}
],
"shared": [
{
"slug": "collection-and-safeguards",
"sha256": "37709cf9978a698026492b29f2095996c462e098a74f082a6b3c3a3a7b38ecab",
"previousSha256": "8610ed8df6a24cf138f9e6e2c09060db2aab4c0b1259ca0168e581e3fb964e52",
"revisionNote": "Stage 01 separation: baseline establishment moved to baseline.mdx; DORA candidates are optional. Event/privacy and outcome safeguards retained."
},
{
"slug": "synthetic-example",
"sha256": "24af68ff4fd61159d1c0557ed0f8f8462470d56c6c83816eb93b47fb04149fde"
}
]
}
+3 -8
View File
@@ -28,11 +28,6 @@
]
},
"pages": [
{
"id": "index",
"title": "AI adoption strategy",
"purpose": "Govern skills first; outcomes before activity; explicit target status."
},
{
"id": "target-operating-model",
"title": "Target operating model",
@@ -55,8 +50,8 @@
},
{
"id": "measurement",
"title": "Measurement",
"purpose": "Full KPI contracts, minimal events, illustrative calculations, privacy and limits."
"title": "Skills Measurement",
"purpose": "Which KPIs to collect during skills adoption, how to calculate them and when to report."
},
{
"id": "skills-maintenance",
@@ -66,7 +61,7 @@
{
"id": "roadmap",
"title": "Roadmap",
"purpose": "Evidence-gated phases, no promised dates or budgets."
"purpose": "Assess current code quality and delivery processes, close critical gaps, then pilot, expand and sustain AI adoption."
}
],
"diagram": {
+34
View File
@@ -0,0 +1,34 @@
import test from 'node:test';
import assert from 'node:assert/strict';
import {readFileSync} from 'node:fs';
const read = path => readFileSync(path, 'utf8');
test('Baseline is workflow-scoped, evidence-bound and distinct from the optional registry', () => {
const page = read('docs/strategy/baseline.mdx');
for (const heading of ['Understand the current workflow','Select relevant metrics, with reasons','Agree feasible evidence','Record the starting position','Keep later evaluation comparable']) assert(page.includes(`## ${heading}`));
for (const text of ['not a mandatory company-wide baseline','no actual baseline values or approved thresholds','lawful basis','privacy','retention','source coverage','**Available:**','**Unavailable:**','not causal ROI','selected-but-unavailable']) assert(page.includes(text), text);
assert(page.indexOf('<ArchifyDiagram') < page.indexOf('## Understand'));
assert(!page.includes('25%'));
for (const doc of ['measurement/index','measurement/collection-and-safeguards','skills-adoption','skills-maintenance','skills-governance']) assert(page.includes(`./${doc}.mdx`));
const registry = read('docs/strategy/measurement/index.mdx');
assert(registry.includes('pagination_next: baseline'));
assert(page.includes('pagination_prev: measurement/index'));
assert(page.includes('pagination_next: skills-governance'));
});
test('workflow application has one home and shared safety remains explicit', () => {
const registry = read('docs/strategy/measurement/index.mdx');
const shared = read('docs/strategy/measurement/collection-and-safeguards.mdx');
const adoption = read('docs/strategy/skills-adoption.mdx');
const maintenance = read('docs/strategy/skills-maintenance.mdx');
assert(!registry.includes('Measure the pilot'));
assert(!shared.includes('Track all five'));
assert(!shared.includes('Before a pilot, freeze'));
assert(shared.includes('id') && shared.includes('{#baseline-and-interpretation}')); // Existing inbound anchor survives relocation.
for (const marker of ['transport retries','quarantined','Late arrivals','Unknown version stays null','30 days','12 months','below five people','No raw prompts','Consent is not presumed']) assert(shared.includes(marker),marker);
assert(adoption.includes('not a mandatory pilot bundle'));
assert(adoption.includes('What a pilot report looks like'));
assert(maintenance.includes('Keep selected evidence useful'));
assert(maintenance.includes('versioned corrections'));
assert(adoption.includes('**Next:** [Maintain skills using the agreed evidence →](./skills-maintenance.mdx)'));
});
+13 -3
View File
@@ -88,7 +88,10 @@ const fs = require('node:fs');
if (format.startsWith('svg')) {
const valid = await page.evaluate(xml => {
const doc = new DOMParser().parseFromString(xml, 'image/svg+xml');
return !doc.querySelector('parsererror') && doc.documentElement.localName === 'svg' && doc.querySelectorAll('text').length > 0;
if (doc.querySelector('[data-node-id="humans"], [data-edge-id="human-direction"]')) return false;
if (![...doc.querySelectorAll('[data-node-id="agent"] text')].some(n => n.textContent === 'Human Controlled')) return false;
if (doc.querySelectorAll('[data-node-id]').length !== 17 || doc.querySelectorAll('path[data-edge-id]').length !== 24) return false;
return !doc.querySelector('parsererror') && doc.documentElement.localName === 'svg' && doc.querySelectorAll('text').length > 0 && doc.querySelector('#eldorado-cycle-export')?.textContent.includes('stroke-dasharray: 3 9');
}, bytes.toString());
assert(valid, format);
} else {
@@ -117,10 +120,17 @@ const fs = require('node:fs');
await close.focus(); await page.keyboard.press('Escape');
assert(await opener.evaluate(n => n === document.activeElement));
await iframe.scrollIntoViewIfNeeded();
await page.evaluate(() => scrollTo(0, 0));
await page.evaluate(() => scrollTo({top: 0, behavior: 'instant'}));
await page.evaluate(() => new Promise(resolve => requestAnimationFrame(() => requestAnimationFrame(resolve))));
await page.screenshot({path:`${output}/${width}.png`, fullPage:true});
await frame.locator('#btn-theme').click(); await theme('dark');
await page.locator('.strategy-content a[href$="/strategy/target-operating-model/"]').filter({visible:true}).click();
// Exercise keyboard navigation without racing the portal's smooth scroll.
await page.locator('.strategy-content a[href$="/strategy/roadmap/"]').filter({visible:true}).focus();
await page.keyboard.press('Enter');
await page.waitForURL('**/strategy/roadmap/');
await page.goBack({waitUntil:'domcontentloaded'});
await page.waitForURL('**/strategy/target-operating-model/');
await page.getByRole('heading', {name:'Target operating model', exact:true, level:1}).waitFor();
const next = page.locator(`.archify-panel--story[data-diagram="strategy-target"] > .story-${width > 700 ? 'desktop' : 'mobile'}`);
await next.scrollIntoViewIfNeeded();
await (await (await next.elementHandle()).contentFrame()).waitForFunction(() => document.documentElement.dataset.theme === 'dark');
+79
View File
@@ -0,0 +1,79 @@
const {chromium} = require('playwright');
const assert = require('node:assert/strict');
const fs = require('node:fs');
(async () => {
const base = process.argv[2] || 'http://127.0.0.1:4173';
const prefix = '/eldorado-v1/documentation';
const manifest = JSON.parse(fs.readFileSync('research/ai-adoption/measurement-migration.json','utf8'));
const output = `.cache/metric-pages-${process.argv[3] || 'local'}`;
fs.mkdirSync(output,{recursive:true});
const browser = await chromium.launch({headless:true,executablePath:process.env.PLAYWRIGHT_CHROMIUM_EXECUTABLE,args:['--no-sandbox']});
const results = [];
try {
for (const width of [1440,390]) {
const context = await browser.newContext({viewport:{width,height:900}});
try {
const page = await context.newPage();
const errors = [];
page.on('pageerror',e => errors.push(e.message));
for (const m of manifest.metrics) {
const url = `${base}${prefix}${m.url}`;
assert.equal((await page.goto(url,{waitUntil:'networkidle'})).status(),200);
assert.equal(await page.locator('article h1').innerText(),m.title);
assert.equal(await page.locator('link[rel="canonical"]').getAttribute('href'),`https://pages.apps.lego-cloud.eu${prefix}${m.url}`);
const table = page.locator('article table');
assert.equal(await table.count(),1);
assert.equal(await table.locator('tbody tr').count(),11);
const article = await page.locator('article').innerText();
assert(article.includes(m.status === 'prototype' ? 'Prototype calculation' : 'Unimplemented metric'));
assert(article.includes('no live telemetry'));
assert.equal(await page.locator('.breadcrumbs a').filter({hasText:'Measurement'}).getAttribute('href'),`${prefix}/strategy/measurement/`);
assert(!await page.evaluate(() => document.documentElement.scrollWidth > innerWidth));
await page.goto(`${base}${prefix}/strategy/reference/measurement-contracts/#${m.oldAnchor}`,{waitUntil:'networkidle'});
await page.waitForURL(url);
await page.locator('article h1').waitFor();
results.push({width,metric:m.oldAnchor,canonical:true,redirect:true,fields:11});
}
for (const suffix of ['', '#unknown-anchor', '#__proto__']) {
await page.goto(`${base}${prefix}/strategy/reference/measurement-contracts/${suffix}`,{waitUntil:'networkidle'});
await page.waitForURL(`${base}${prefix}/strategy/measurement/`);
}
for (const [anchor,target] of [
['collection-and-safeguards','collection-and-safeguards/'],
['decide-what-counts-before-counting','collection-and-safeguards/#decide-what-counts-before-counting'],
['baseline-and-interpretation','collection-and-safeguards/#baseline-and-interpretation'],
['event-and-privacy-contract','collection-and-safeguards/#event-and-privacy-contract'],
['run-the-synthetic-measurement-example','synthetic-example/'],
['metric-contracts','#metric-definitions'],
]) {
await page.goto(`${base}${prefix}/strategy/reference/measurement-contracts/#${anchor}`,{waitUntil:'networkidle'});
await page.waitForURL(`${base}${prefix}/strategy/measurement/${target}`);
if (target.includes('#')) await page.locator(`#${target.split('#')[1]}`).waitFor();
}
await page.goto(`${base}${prefix}/strategy/measurement/supported-bundle-coverage/`,{waitUntil:'networkidle'});
await page.locator('.breadcrumbs a').filter({hasText:'Measurement'}).click();
await page.waitForURL(`${base}${prefix}/strategy/measurement/`);
if (width < 997) await page.getByRole('button',{name:'Toggle navigation bar'}).click();
const menu = page.locator('.theme-doc-sidebar-menu').filter({visible:true});
const category = menu.locator('.theme-doc-sidebar-item-category').filter({has:page.getByRole('link',{name:'Measurement',exact:true})}).last();
const caret = category.locator(':scope > .menu__list-item-collapsible > button.menu__caret');
await caret.click();
await category.getByRole('link',{name:'Validated task success',exact:true}).waitFor({state:'hidden'});
await caret.focus(); await page.keyboard.press('Enter');
await category.getByRole('link',{name:'Validated task success',exact:true}).waitFor({state:'visible'});
await menu.getByRole('link',{name:'Measurement',exact:true}).click();
await page.waitForURL(`${base}${prefix}/strategy/measurement/`);
await page.locator('article h1').waitFor();
if (width < 997) await page.getByRole('button',{name:'Close navigation bar'}).waitFor({state:'hidden'});
await page.locator('#metric-definitions').scrollIntoViewIfNeeded();
await page.screenshot({path:`${output}/${width}-index.png`});
await page.goto(`${base}${prefix}/strategy/measurement/supported-bundle-coverage/`,{waitUntil:'networkidle'});
await page.screenshot({path:`${output}/${width}-metric.png`,fullPage:true});
assert.deepEqual(errors,[]);
} finally {await context.close();}
}
assert.equal(results.length,32);
fs.writeFileSync(`${output}/results.json`,JSON.stringify(results,null,2));
console.log('PASS: 16 metric pages × 2 widths; canonical metadata, contract fields, status, all legacy metric/shared/fallback redirects and linked Measurement keyboard navigation');
} finally {await browser.close();}
})().catch(e => {console.error(e);process.exitCode=1;});
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const {chromium} = require('playwright');
const assert = require('node:assert/strict');
const fs = require('node:fs');
const views = {
'strategy-roadmap': ['skills','autonomy'],
'strategy-roadmap-adoption': ['delivery','remaining'],
'strategy-roadmap-loop': ['understand','baseline','topology','use','collect','reassess'],
};
(async () => {
const base = process.argv[2] || 'http://127.0.0.1:4173';
const output = `.cache/roadmap-timeline-${process.argv[3] || 'local'}`;
fs.mkdirSync(output, {recursive:true});
const browser = await chromium.launch({headless:true, executablePath:process.env.PLAYWRIGHT_CHROMIUM_EXECUTABLE, args:['--no-sandbox']});
const results = [];
const inspect = async (frame, name, vertical) => {
await frame.locator('svg[role="img"]').waitFor();
const geometry = await frame.locator('svg[role="img"]').evaluate(svg => ({
width:innerWidth, height:innerHeight,
edges:[...svg.querySelectorAll('path[data-edge-id]')].map(p => ({id:p.dataset.edgeId,box:p.getBoundingClientRect().toJSON()})),
cards:[...svg.querySelectorAll('[data-node-id]')].map(node => ({
id:node.dataset.nodeId, box:node.querySelector('rect').getBoundingClientRect().toJSON(),
number:node.querySelector('[data-stage-number]').textContent,
text:[...node.querySelectorAll('text')].map(text => ({value:text.textContent, box:text.getBoundingClientRect().toJSON(), size:parseFloat(getComputedStyle(text).fontSize)*text.getScreenCTM().a}))
}))
}));
const ids=views[name];
geometry.cards.sort((a,b)=>ids.indexOf(a.id)-ids.indexOf(b.id));
assert.deepEqual(geometry.cards.map(n => n.id), ids);
assert.deepEqual(geometry.cards.map(n => n.number), ids.length === 6 ? ids.map((_,i)=>`Step ${i+1}`) : name === 'strategy-roadmap' ? ['Stage 1','Stage 2'] : ['First','Then']);
assert.equal(geometry.edges.length,ids.length===6?6:1);
if(ids.length===6) assert(geometry.edges.some(e=>e.id==='repeat'));
for(const edge of geometry.edges) assert(edge.box.left>=0 && edge.box.right<=geometry.width+1 && edge.box.top>=0 && edge.box.bottom<=geometry.height+1, `clipped edge ${name} ${edge.id}`);
for (const [index, card] of geometry.cards.entries()) {
assert.equal(card.text.length,3);
assert(card.box.left >= 0 && card.box.top >= 0 && card.box.right <= geometry.width+1 && card.box.bottom <= geometry.height+1, `outside iframe ${name} ${card.id}`);
for(const text of card.text) {
assert(text.size>=13, `small text ${name} ${card.id}: ${text.size}`);
assert(text.box.left>=card.box.left && text.box.right<=card.box.right+1 && text.box.top>=card.box.top && text.box.bottom<=card.box.bottom+1, `clipped text ${name} ${card.id}`);
}
for(let t=1;t<card.text.length;t++) assert(card.text[t-1].box.bottom<card.text[t].box.top,`text overlap ${card.id}`);
if(index && vertical) {assert.equal(geometry.cards[index-1].box.x,card.box.x);assert(geometry.cards[index-1].box.bottom<card.box.top);}
}
return geometry;
};
try {
for(const width of [1440,1024,390,320]) {
const context=await browser.newContext({viewport:{width,height:1000},colorScheme:'light'});
try {
const page=await context.newPage(); const errors=[]; page.on('pageerror',e=>errors.push(e.message));
assert.equal((await page.goto(`${base}/eldorado-v1/documentation/strategy/roadmap/`,{waitUntil:'networkidle'})).status(),200);
await page.addStyleTag({content:'html {scroll-behavior:auto !important;}'});
assert.equal(await page.locator('.archify-panel--story').count(),3);
for(const name of Object.keys(views)) {
const panel=page.locator(`[data-diagram="${name}"]`);
const iframe=panel.locator(width<1100?'.story-mobile':'.story-desktop');
await iframe.scrollIntoViewIfNeeded();
const frame=await (await iframe.elementHandle()).contentFrame();
await frame.locator('svg[role="img"]').waitFor();
const opener=panel.getByRole('button',{name:/^Expand /});
for(const theme of ['light','dark']) {
const frameTop=await iframe.evaluate(n=>n.getBoundingClientRect().top+scrollY);
await page.evaluate(y=>scrollTo({top:y-120,behavior:'instant'}),frameTop);
if(await frame.locator('html').getAttribute('data-theme')!==theme) await frame.locator('#btn-theme').click();
await page.waitForFunction(t=>document.documentElement.dataset.theme===t,theme);
const inline=await inspect(frame,name,width<1100);
await frame.locator('#btn-preset').focus();await page.keyboard.press('Enter');
await frame.locator('[data-preset-value="blueprint"]').focus();await page.keyboard.press('Enter');
await frame.waitForFunction(()=>document.documentElement.dataset.preset==='blueprint');
await inspect(frame,name,width<1100);
await frame.locator('#btn-preset').focus();await page.keyboard.press('Enter');
await frame.locator('[data-preset-value="classic"]').focus();await page.keyboard.press('Enter');
await frame.waitForFunction(()=>document.documentElement.dataset.preset==='classic');
await frame.locator('#btn-export').focus();await page.keyboard.press('Enter');
await frame.locator('[data-format="svg"]').focus();
const [download]=await Promise.all([page.waitForEvent('download'),page.keyboard.press('Enter')]);
assert.equal(await download.failure(),null);
const exported=`${output}/${width}-${theme}-${name}.svg`;
await download.saveAs(exported);
const svg=fs.readFileSync(exported,'utf8');
for(const id of views[name]) assert(svg.includes(`data-node-id="${id}"`));
assert(svg.includes('eldorado-roadmap-typography'));
await panel.screenshot({path:`${output}/${width}-${theme}-${name}-inline.png`});
// Scroll each card into the real viewport: tall iframe captures alone
// may contain compositor blanks even when DOM geometry is correct.
for(const card of inline.cards) {
const top=await iframe.evaluate(n=>n.getBoundingClientRect().top+scrollY);
await page.evaluate(y=>scrollTo({top:y,behavior:'instant'}),top+card.box.top-100);
await page.screenshot({path:`${output}/${width}-${theme}-${name}-${card.id}.png`});
}
await opener.focus();await page.keyboard.press('Enter');
const close=panel.getByRole('button',{name:'Close full-screen diagram',exact:true});await close.waitFor({state:'visible'});
const fullIframe=panel.locator('dialog iframe');
const fullscreen=await (await fullIframe.elementHandle()).contentFrame();
await fullscreen.waitForFunction(t=>document.documentElement.dataset.theme===t,theme);
const expanded=await inspect(fullscreen,name,width<1000);
await page.screenshot({path:`${output}/${width}-${theme}-${name}-fullscreen.png`});
await close.focus();await page.keyboard.press('Escape');
await fullIframe.waitFor({state:'detached'});assert(await opener.evaluate(n=>n===document.activeElement));
results.push({width,theme,name,inline,expanded});fs.writeFileSync(`${output}/results.json`,JSON.stringify(results,null,2));
}
}
assert(!await page.evaluate(()=>document.documentElement.scrollWidth>innerWidth));assert.deepEqual(errors,[]);
} finally {await context.close();}
}
assert.equal(results.length,24);
for(const viewport of [{width:390,height:667},{width:320,height:568}]) {
const context=await browser.newContext({viewport});
try {
const page=await context.newPage();await page.goto(`${base}/eldorado-v1/documentation/strategy/roadmap/`,{waitUntil:'networkidle'});
await page.addStyleTag({content:'html {scroll-behavior:auto !important;}'});
for(const name of Object.keys(views)) {
const panel=page.locator(`[data-diagram="${name}"]`), opener=panel.getByRole('button',{name:/^Expand /});
await opener.focus();await page.keyboard.press('Enter');const modal=panel.locator('dialog'), close=modal.getByRole('button',{name:'Close full-screen diagram',exact:true});await close.waitFor({state:'visible'});
const iframe=modal.locator('iframe'), frame=await (await iframe.elementHandle()).contentFrame();
const geometry=await inspect(frame,name,true);
assert(await modal.evaluate(n=>n.scrollHeight>n.clientHeight),'short fullscreen must scroll');
for(const card of geometry.cards) {
await modal.evaluate((n,y)=>{n.scrollTop=y;},card.box.top);
const b=await iframe.boundingBox(), t=await modal.locator('.archify-modal-toolbar').boundingBox(), c=await close.boundingBox();
assert(c.y>=0 && c.y+c.height<=viewport.height);
assert(b.y+card.box.top>=t.y+t.height-1 && b.y+card.box.bottom<=viewport.height+1,`unreachable ${name} ${card.id}`);
}
await modal.evaluate(n=>{n.scrollTop=0;});
for(const selector of ['#btn-theme','#btn-preset','#btn-export']) {
const control=frame.locator(selector), b=await control.boundingBox();assert(b.x>=0 && b.x+b.width<=viewport.width && b.y>=0 && b.y+b.height<=viewport.height);await control.click();if(selector!=='#btn-theme')await control.click();
}
await close.focus();await page.keyboard.press('Escape');await iframe.waitFor({state:'detached'});assert(await opener.evaluate(n=>n===document.activeElement));
await page.keyboard.press('Enter');await close.waitFor({state:'visible'});await close.click();await iframe.waitFor({state:'detached'});assert(await opener.evaluate(n=>n===document.activeElement));
results.push({viewport,name,scrollable:geometry});fs.writeFileSync(`${output}/results.json`,JSON.stringify(results,null,2));
}
} finally {await context.close();}
}
assert.equal(results.length,30);
console.log('PASS 48 diagram contexts: three views × four widths × light/dark × inline/fullscreen; plus six short-phone scrolling/keyboard contexts.');
} finally {await browser.close();}
})().catch(error=>{console.error(error);process.exitCode=1;});
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const {chromium} = require('playwright');
const assert = require('node:assert/strict');
const fs = require('node:fs');
(async () => {
const base = process.argv[2] || 'http://127.0.0.1:4173';
const output = `.cache/roadmap-${process.argv[3] || 'local'}`;
fs.mkdirSync(output, {recursive:true});
const browser = await chromium.launch({headless:true, executablePath:process.env.PLAYWRIGHT_CHROMIUM_EXECUTABLE, args:['--no-sandbox']});
const results = [];
try {
// Intermediate widths must use the readable vertical Roadmap, not shrink the loop.
for (const width of [768, 1024]) {
const context = await browser.newContext({viewport:{width,height:1000}, colorScheme:'light'});
try {
const page = await context.newPage();
const errors = [];
page.on('pageerror', error => errors.push(error.message));
const response = await page.goto(`${base}/eldorado-v1/documentation/strategy/roadmap/`, {waitUntil:'networkidle'});
assert.equal(response.status(), 200);
const panel = page.locator('.archify-panel--story[data-diagram="strategy-roadmap"]');
const iframe = panel.locator('.story-mobile');
assert(await iframe.isVisible(), `${width}: vertical Roadmap iframe must be visible`);
assert(!await panel.locator('.story-desktop').isVisible(), `${width}: horizontal Roadmap must be hidden`);
const frame = await (await iframe.elementHandle()).contentFrame();
await frame.locator('svg[role="img"]').waitFor();
const geometry = await frame.locator('svg[role="img"]').evaluate(svg => ({
width:innerWidth, height:innerHeight,
overflow:document.documentElement.scrollWidth > innerWidth || document.documentElement.scrollHeight > innerHeight,
nodes:[...svg.querySelectorAll('[data-node-id]')].map(node => ({
id:node.dataset.nodeId, box:node.querySelector('rect').getBoundingClientRect().toJSON(),
text:[...node.querySelectorAll('text')].map(t => ({text:t.textContent, box:t.getBoundingClientRect().toJSON(), size:parseFloat(getComputedStyle(t).fontSize)*t.getScreenCTM().a}))
})).sort((a,b) => a.box.y-b.box.y || a.box.x-b.box.x)
}));
assert.deepEqual(geometry.nodes.map(n => n.id), ['skills','autonomy']);
for (const [index, card] of geometry.nodes.entries()) {
assert(card.text.length > 0, `${width}: missing text in ${card.id}`);
assert(card.box.left >= 0 && card.box.top >= 0 && card.box.right <= geometry.width + 1 && card.box.bottom <= geometry.height + 1, `${width}: card outside iframe: ${card.id}`);
for (const t of card.text) {
assert(t.box.left >= card.box.left && t.box.right <= card.box.right + 1 && t.box.top >= card.box.top && t.box.bottom <= card.box.bottom + 1, `${width}: clipped ${card.id} ${t.text}`);
assert(t.size >= 11, `${width}: small ${card.id} ${t.text}: ${t.size}`);
}
if (index) {
const previous = geometry.nodes[index - 1].box;
assert.equal(previous.x, card.box.x);
assert(previous.bottom < card.box.top, `${width}: stages must flow vertically`);
}
}
assert(!geometry.overflow, `${width}: iframe overflow`);
assert(!await page.evaluate(() => document.documentElement.scrollWidth > innerWidth), `${width}: page overflow`);
assert.deepEqual(errors, []);
results.push({width, geometry, responsiveReadability:true});
fs.writeFileSync(`${output}/results.json`, JSON.stringify(results,null,2));
} finally {await context.close();}
}
for (const width of [1440, 390, 320]) {
const context = await browser.newContext({viewport:{width,height:1000}, colorScheme:'light'});
const page = await context.newPage();
const errors = [];
page.on('pageerror', error => errors.push(error.message));
const response = await page.goto(`${base}/eldorado-v1/documentation/strategy/roadmap/`, {waitUntil:'networkidle'});
assert.equal(response.status(), 200);
assert.equal(await page.locator('h1').innerText(), 'Roadmap');
const headings = page.locator('.strategy-content > h2');
assert.deepEqual((await headings.allTextContents()).map(s => s.replace(/\u200b/g, '')), ['Two stages toward Target','Stage 1: Delivery first','Improve within each phase','Delivery in practice']);
const text = await page.locator('.strategy-content').innerText();
for (const marker of ['Humans direct, guide and review throughout', 'Delivery keeps improving', 'system-logic source', 'baseline', 'Target operating model']) assert(text.includes(marker), marker);
assert(!text.includes('Supporting gate evidence and hold conditions\n\nThese are'));
if (width < 700) await page.getByRole('button', {name:'Toggle navigation bar'}).click();
const menu = page.locator('.theme-doc-sidebar-menu .menu__link').filter({visible:true});
await menu.first().waitFor({state:'visible'});
assert.deepEqual((await menu.allTextContents()).slice(0,2), ['Target','Roadmap']);
if (width < 700) await page.getByRole('button', {name:'Close navigation bar'}).click();
const panel = page.locator('.archify-panel--story').first();
const iframe = panel.locator(width > 700 ? '.story-desktop' : '.story-mobile');
await iframe.scrollIntoViewIfNeeded();
const frame = await (await iframe.elementHandle()).contentFrame();
await frame.locator('svg[role="img"]').waitFor();
const checkCards = async () => {
const cards = await frame.locator('svg[role="img"] [data-node-id]').evaluateAll(nodes => nodes.map(node => {
const box = node.querySelector('rect').getBoundingClientRect();
return {id:node.dataset.nodeId, box:box.toJSON(), text:[...node.querySelectorAll('text')].map(t => ({text:t.textContent, box:t.getBoundingClientRect().toJSON(), size:parseFloat(getComputedStyle(t).fontSize)*t.getScreenCTM().a}))};
}));
for (const card of cards) for (const t of card.text) {
assert(t.box.left >= card.box.left && t.box.right <= card.box.right + 1 && t.box.top >= card.box.top && t.box.bottom <= card.box.bottom + 1, `${width}: clipped ${card.id} ${t.text}`);
assert(t.size >= 11, `${width}: small ${card.id} ${t.text}: ${t.size}`);
}
return cards;
};
await checkCards();
const geometry = await frame.locator('svg[role="img"]').evaluate(svg => ({
nodes:[...svg.querySelectorAll('[data-node-id]')].map(n => ({id:n.dataset.nodeId,...n.getBoundingClientRect().toJSON()})).sort((a,b) => a.y-b.y || a.x-b.x),
width:innerWidth, height:innerHeight,
minLabel:Math.min(...[...svg.querySelectorAll('text[data-node-label]')].map(n => parseFloat(getComputedStyle(n).fontSize)*n.getScreenCTM().a))
}));
assert.deepEqual(geometry.nodes.map(n => n.id), ['skills','autonomy']);
for (const n of geometry.nodes) assert(n.x >= 0 && n.y >= 0 && n.right <= geometry.width + 1 && n.bottom <= geometry.height + 1);
assert(geometry.minLabel >= 10, `readable node labels: ${geometry.minLabel}`);
for (let i=1; i<geometry.nodes.length; i++) {
const a=geometry.nodes[i-1], b=geometry.nodes[i];
if(width > 700) {assert.equal(a.y,b.y); assert(a.right < b.x);}
else {assert.equal(a.x,b.x); assert(a.bottom < b.y);}
}
// Portal -> diagram and diagram -> portal are both part of the contract.
if (width <= 700) await page.getByRole('button', {name:'Toggle navigation bar'}).click();
for (let attempt=0; attempt<3; attempt++) {
await page.getByRole('button', {name:/Switch between dark and light mode/}).filter({visible:true}).click();
if (await page.locator('html').getAttribute('data-theme') === 'dark') break;
}
if (width <= 700) await page.getByRole('button', {name:'Close navigation bar'}).click();
await frame.waitForFunction(() => document.documentElement.dataset.theme === 'dark');
await frame.locator('#btn-theme').click();
await page.waitForFunction(() => document.documentElement.dataset.theme === 'light');
await frame.locator('#btn-theme').click();
await page.waitForFunction(() => document.documentElement.dataset.theme === 'dark');
await checkCards();
await frame.locator('#btn-theme').click();
await page.waitForFunction(() => document.documentElement.dataset.theme === 'light');
for (const preset of ['blueprint','classic']) {
await frame.locator('#btn-preset').click();
await frame.locator(`[data-preset-value="${preset}"]`).click();
assert.equal(await frame.locator('html').getAttribute('data-preset'), preset);
await checkCards();
}
await frame.locator('#btn-export').click();
const [download] = await Promise.all([page.waitForEvent('download'), frame.locator('[data-format="svg"]').click()]);
assert.equal(await download.failure(), null);
await download.saveAs(`${output}/${width}.svg`);
assert(fs.readFileSync(`${output}/${width}.svg`, 'utf8').includes('Adopt skills'));
assert(fs.readFileSync(`${output}/${width}.svg`, 'utf8').includes('eldorado-roadmap-typography'));
for (const id of ['skills','autonomy']) {
await frame.locator(`svg[role="img"] [data-node-id="${id}"]`).screenshot({path:`${output}/${width}-${id}-card.png`});
}
const opener = panel.getByRole('button', {name:/^Expand /});
await opener.click();
const close = panel.getByRole('button', {name:'Close full-screen diagram', exact:true});
await close.waitFor({state:'visible'}); assert.equal(await close.innerText(), '×');
await close.click(); assert(await opener.evaluate(n => n === document.activeElement));
await opener.click(); await close.waitFor({state:'visible'}); await page.keyboard.press('Escape');
await page.waitForFunction(() => !document.querySelector('.archify-panel--story dialog').open);
assert(await opener.evaluate(n => n === document.activeElement));
assert(!await page.evaluate(() => document.documentElement.scrollWidth > innerWidth));
await page.evaluate(() => scrollTo({top:0, behavior:'instant'}));
await page.screenshot({path:`${output}/${width}-top.png`});
await headings.first().scrollIntoViewIfNeeded();
await page.screenshot({path:`${output}/${width}-assessment.png`});
await page.screenshot({path:`${output}/${width}-full.png`, fullPage:true});
await page.locator('.strategy-content summary').focus();
await page.keyboard.press('Enter');
await page.waitForFunction(() => document.querySelector('.strategy-content details').open);
await page.locator('.strategy-content details p').last().waitFor({state:'visible'});
assert((await page.locator('.strategy-content details').innerText()).includes('exact-artifact approvals'));
const links = await page.locator('.strategy-content a').evaluateAll(nodes => nodes.filter(n => !n.classList.contains('hash-link')).map(n => n.href));
for (const href of [...new Set(links)]) {
const r = await page.goto(href, {waitUntil:'networkidle'}); assert.equal(r.status(), 200);
assert.equal(page.url(), href);
}
assert.deepEqual(errors, []);
results.push({width, geometry, links:links.length, controls:true, export:true, sidebar:true, visibleAssessment:true});
fs.writeFileSync(`${output}/results.json`, JSON.stringify(results,null,2));
await context.close();
}
console.log(`PASS ${results.length} Roadmap viewports: three-level story, sidebar, diagram geometry, controls, export and links`);
} finally {await browser.close();}
})().catch(error => {console.error(error); process.exitCode = 1;});
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const {chromium} = require('playwright');
const assert = require('node:assert/strict');
const fs = require('node:fs');
(async () => {
const base = process.argv[2] || 'http://127.0.0.1:4173';
const output = `.cache/cycle-${process.argv[3] || 'local'}`;
fs.mkdirSync(output, {recursive:true});
const browser = await chromium.launch({headless:true, executablePath:process.env.PLAYWRIGHT_CHROMIUM_EXECUTABLE, args:['--no-sandbox']});
const results = [];
try {
for (const width of [1440, 390, 320]) {
const context = await browser.newContext({viewport:{width,height:1000}, colorScheme:'light'});
const page = await context.newPage();
await page.goto(`${base}/eldorado-v1/documentation/`, {waitUntil:'networkidle'});
if (width < 700) await page.getByRole('button', {name:'Toggle navigation bar'}).click();
const nav = page.getByRole('link', {name:'Strategy', exact:true}).filter({visible:true});
assert((await nav.getAttribute('href')).endsWith('/strategy/target-operating-model/'));
await nav.click();
await page.waitForURL('**/strategy/target-operating-model/');
for (const route of ['target-operating-model/', '']) {
await page.goto(`${base}/eldorado-v1/documentation/strategy/${route}`, {waitUntil:'networkidle'});
await page.waitForURL('**/strategy/target-operating-model/');
if (width < 700) await page.getByRole('button', {name:'Toggle navigation bar'}).click();
const menu = page.locator('.theme-doc-sidebar-menu .menu__link').filter({visible:true});
await menu.first().waitFor({state:'visible'});
assert.deepEqual(await menu.allTextContents(), ['Target', 'Roadmap', 'Stage - 01 - Skills Adoption', 'Stage - 02 - Autonomous Agent']);
assert((await menu.nth(0).getAttribute('href')).endsWith('/strategy/target-operating-model/'));
assert((await menu.nth(1).getAttribute('href')).endsWith('/strategy/roadmap/'));
assert.equal(await menu.filter({hasText:/^Target$/}).count(), 1);
await page.screenshot({path:`${output}/${width}-${route ? 'target' : 'landing'}-navigation.png`,fullPage:true,animations:'disabled'});
await menu.nth(1).click();
await page.waitForURL('**/strategy/roadmap/');
await page.getByRole('heading', {level:1,name:'Roadmap',exact:true}).waitFor();
await page.goBack({waitUntil:'domcontentloaded'});
await page.waitForURL('**/strategy/target-operating-model/');
const iframe = page.locator(`.archify-panel--story > .story-${width > 700 ? 'desktop' : 'mobile'}`);
await iframe.scrollIntoViewIfNeeded();
const frame = await (await iframe.elementHandle()).contentFrame();
await frame.locator('svg[role="img"]').waitFor();
const metrics = await frame.evaluate(() => {
const svg = document.querySelector('svg[role="img"]');
const labels = [...svg.querySelectorAll('text[data-node-label]')].map(n => ({text:n.textContent,px:parseFloat(getComputedStyle(n).fontSize)*n.getScreenCTM().a}));
const edges = [...svg.querySelectorAll('path[data-edge-id^="stage-"]')].map(n => [n.dataset.edgeFrom,n.dataset.edgeTo,n.getAttribute('marker-end')]);
const overflow = [...svg.querySelectorAll('[data-node-id]')].flatMap(n => {
const box = n.querySelector('rect').getBoundingClientRect();
return [...n.querySelectorAll('text')].filter(t => {const b=t.getBoundingClientRect();return b.left<box.left||b.right>box.right||b.top<box.top||b.bottom>box.bottom;}).map(t=>t.textContent);
});
const relationships = [...svg.querySelectorAll('path[data-edge-id]')].map(n => ({id:n.dataset.edgeId,from:n.dataset.edgeFrom,to:n.dataset.edgeTo,dash:getComputedStyle(n).strokeDasharray,arrow:n.getAttribute('marker-end')}));
const nodes = [...svg.querySelectorAll('[data-node-id]')].map(n => {const r=n.querySelector('rect').getBoundingClientRect();return {id:n.dataset.nodeId,x:r.x+r.width/2,y:r.y+r.height/2};});
return {labels,edges,overflow,relationships,nodes};
});
const ids = ['scope','architecture','ui-ux','planning','delivery','uat','security','releases'];
assert.deepEqual(metrics.edges.map(e=>e.slice(0,2)), ids.map((id,i)=>[id,ids[(i+1)%ids.length]]));
assert(metrics.edges.every(e=>e[2]?.startsWith('url(')), 'all stages must have arrowheads');
assert.equal(metrics.nodes.length, 17);
assert.equal(metrics.labels.filter(n => n.text === 'AI Agent').length, 8);
assert(!metrics.labels.some(n => /code[ -]agent/i.test(n.text)));
assert((await page.locator('.strategy-content').innerText()).includes('human-controlled AI Agent'));
assert(!metrics.nodes.some(n=>n.id==='humans'));
assert.equal(await frame.locator('[data-node-id="agent"] text').allTextContents().then(texts=>texts.includes('Human Controlled')), true);
assert.equal(metrics.relationships.length, 24);
const governs = metrics.relationships.filter(e=>e.id.startsWith('govern-'));
const contributions = metrics.relationships.filter(e=>e.id.startsWith('contribute-'));
assert.deepEqual(governs.map(e=>[e.from,e.to]), ids.map(id=>['agent',id]));
assert.deepEqual(contributions.map(e=>[e.from,e.to]), ids.map(id=>[`code-${id}`,id]));
assert(governs.every(e=>e.dash==='3px, 9px' && e.arrow?.startsWith('url(')));
assert(contributions.every(e=>e.dash==='12px, 8px' && e.arrow?.startsWith('url(')));
assert(!metrics.relationships.some(e=>e.id==='human-direction' || e.from==='humans' || e.to==='humans'));
if (width > 700) {
const agent = metrics.nodes.find(n=>n.id==='agent');
const phases = metrics.nodes.filter(n=>ids.includes(n.id));
for (const axis of ['x','y']) assert(Math.abs(agent[axis]-(Math.min(...phases.map(n=>n[axis]))+Math.max(...phases.map(n=>n[axis])))/2)<1);
for (const id of ids) {
const phase=phases.find(n=>n.id===id), code=metrics.nodes.find(n=>n.id===`code-${id}`);
assert(Math.hypot(code.x-agent.x,code.y-agent.y)>Math.hypot(phase.x-agent.x,phase.y-agent.y));
}
}
assert(metrics.labels.every(n=>n.px>=14), JSON.stringify(metrics.labels));
assert.deepEqual(metrics.overflow, []);
await frame.locator('#btn-export').click();
const [download] = await Promise.all([page.waitForEvent('download'), frame.locator('[data-format="svg"]').click()]);
assert.equal(await download.failure(), null);
const exportPath = `${output}/${width}-${route ? 'target' : 'landing'}.svg`;
await download.saveAs(exportPath);
const exported = fs.readFileSync(exportPath, 'utf8');
assert.equal((exported.match(/>AI Agent<\/text>/g) || []).length, 8);
assert(!/code[ -]agent/i.test(exported));
assert(exported.includes('Autonomous agent') && exported.includes('Human Controlled'));
assert(!await page.evaluate(()=>document.documentElement.scrollWidth>innerWidth));
await page.evaluate(()=>scrollTo({top:0,behavior:'instant'}));
await page.waitForFunction(()=>scrollY===0);
await page.evaluate(()=>new Promise(resolve=>requestAnimationFrame(()=>requestAnimationFrame(resolve))));
await page.screenshot({path:`${output}/${width}-${route ? 'target' : 'landing'}.png`,fullPage:true});
results.push({width,route,...metrics});
fs.writeFileSync(`${output}/results.json`,JSON.stringify(results,null,2));
}
await context.close();
}
assert.equal(results.length,6);
console.log('PASS 6 cycle routes/viewports: navigation, sidebar order, exact directed loop, arrowheads, >=14px labels, text bounds and no overflow');
} finally {await browser.close();}
})().catch(error=>{console.error(error);process.exitCode=1;});
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const {chromium} = require('playwright');
const assert = require('node:assert/strict');
const fs = require('node:fs');
(async () => {
const base = process.argv[2] || 'http://127.0.0.1:4173';
const output = `.cache/sidebar-browser-${process.argv[3] || 'local'}`;
const {documents} = JSON.parse(fs.readFileSync('.cache/sidebar-coverage.json', 'utf8'));
assert(documents.length > 0);
fs.mkdirSync(output, {recursive:true});
const browser = await chromium.launch({headless:true, executablePath:process.env.PLAYWRIGHT_CHROMIUM_EXECUTABLE, args:['--no-sandbox']});
const results = [];
try {
for (const width of [1440,390,320]) {
const context = await browser.newContext({viewport:{width,height:900}});
try {
const page = await context.newPage();
const errors = [];
page.on('pageerror', e => errors.push(e.message));
const menu = page.locator('.theme-doc-sidebar-menu').filter({visible:true});
const open = async () => {
if (width < 997) await page.getByRole('button', {name:'Toggle navigation bar'}).click();
await menu.waitFor();
};
for (const doc of documents) {
assert.equal((await page.goto(`${base}${doc.route}/`, {waitUntil:'networkidle'})).status(), 200);
await page.locator('article h1').waitFor();
await open();
const links = menu.locator('a[href]:not([role="button"])').filter({visible:true});
const active = await links.evaluateAll((nodes, route) => nodes.filter(n => n.pathname.replace(/\/$/,'') === route).map(n => n.textContent), doc.route);
assert.equal(active.length, 1, `${width}: visible unique owning-sidebar entry for ${doc.route}`);
results.push({width, route:doc.route, visibleEntry:active[0]});
}
// Contribution exposes all legacy maintenance pages without changing routes.
for (const [label, route] of [['Starting point','overview'],['Update and publish','maintain'],['Site configuration','reference']]) {
await page.goto(`${base}/eldorado-v1/documentation/contribution/`, {waitUntil:'networkidle'});
await open();
const toggle = menu.getByRole('button', {name:'Portal maintenance', exact:true});
await toggle.focus();
await page.keyboard.press('Enter');
await menu.getByRole('link', {name:label, exact:true}).click();
await page.waitForURL(`${base}/eldorado-v1/documentation/docs/${route}/`);
await page.locator('article h1').waitFor();
}
const reference = '/eldorado-v1/documentation/strategy/reference/measurement-contracts/';
await page.goto(`${base}${reference}#supported-bundle-coverage`, {waitUntil:'networkidle'});
await page.waitForURL(`${base}/eldorado-v1/documentation/strategy/measurement/supported-bundle-coverage/`);
await page.getByRole('heading', {level:1, name:'Supported bundle coverage', exact:true}).waitFor();
assert((await page.locator('article').innerText()).includes('Supported bundle coverage'));
assert.equal(await page.locator('.breadcrumbs a').filter({hasText:'Stage - 01 - Skills Adoption'}).getAttribute('href'), '/eldorado-v1/documentation/strategy/stage-01-skills-adoption/');
assert((await page.locator('.breadcrumbs').innerText()).includes('Measurement'));
await open();
await menu.getByRole('link', {name:'Supported bundle coverage', exact:true}).waitFor({state:'visible'});
await page.screenshot({path:`${output}/${width}-reference.png`, animations:'disabled'});
assert.deepEqual(errors, []);
} finally {await context.close();}
}
assert.equal(results.length, documents.length * 3);
fs.writeFileSync(`${output}/results.json`, JSON.stringify(results,null,2));
console.log(`PASS: all ${documents.length} docs have visible unique sidebar entries at 3 viewports; Contribution links, Measurement breadcrumbs and reported anchor redirect work`);
} finally {await browser.close();}
})().catch(e => {console.error(e); process.exitCode = 1;});
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const {chromium}=require('playwright');
const fs=require('node:fs');
const path=require('node:path');
const assert=require('node:assert/strict');
(async()=>{
const dir=process.argv[2]||'.cache/skills-candidate';
const browser=await chromium.launch({executablePath:process.env.PLAYWRIGHT_CHROMIUM_EXECUTABLE,args:['--no-sandbox']});
const results=[];
try {
for(const topic of ['measurement','baseline','governance','quality','adoption','maintenance']) for(const width of [1440,1024,390,320]){
const spec=JSON.parse(fs.readFileSync(`diagrams/strategy-${topic}${width<=1100?'-mobile':''}.architecture.json`));
const page=await browser.newPage({viewport:{width:1200,height:1000}});
await page.goto('file://'+path.resolve(`${dir}/${topic}-${width}.svg`));
const measured=await page.locator('svg').evaluate(svg=>{
const v=svg.viewBox.baseVal;const issues=[];
for(const el of svg.querySelectorAll('[data-node-id],path[data-edge-id],g[data-edge-id]')){
const b=el.getBBox();if(b.x<v.x-1||b.y<v.y-1||b.x+b.width>v.x+v.width+1||b.y+b.height>v.y+v.height+1)issues.push(el.getAttribute('data-node-id')||el.getAttribute('data-edge-id'));
}
// Measure the whole rendered label group, including its opaque mask:
// text presence alone cannot detect one label hiding another.
const labels=[...svg.querySelectorAll('g[data-edge-id]')].filter(el=>el.querySelector('text')).map(el=>({id:el.dataset.edgeId,box:el.getBoundingClientRect()}));
const labelOverlaps=[];
for(let i=0;i<labels.length;i++)for(let j=i+1;j<labels.length;j++){
const a=labels[i],b=labels[j];
if(Math.min(a.box.right,b.box.right)>Math.max(a.box.left,b.box.left)&&Math.min(a.box.bottom,b.box.bottom)>Math.max(a.box.top,b.box.top))labelOverlaps.push([a.id,b.id]);
}
return {labelOverlaps,viewBox:[v.width,v.height],nodes:[...svg.querySelectorAll('[data-node-id]')].map(n=>n.dataset.nodeId),edges:[...svg.querySelectorAll('path[data-edge-id]')].map(n=>n.dataset.edgeId),text:svg.textContent,issues};
});
assert.deepEqual(measured.viewBox,spec.meta.viewBox);
assert.deepEqual(measured.nodes.sort(),spec.components.map(n=>n.id).sort());
assert.deepEqual(measured.edges.sort(),spec.connections.map(e=>e.id).sort());
assert.deepEqual(measured.issues,[]);
assert.deepEqual(measured.labelOverlaps,[],`${topic}-${width}: rendered edge labels overlap`);
for(const n of spec.components){assert(measured.text.includes(n.label));assert(measured.text.includes(n.tag));for(const line of n.sublabel.split('\n'))assert(measured.text.includes(line));}
for(const e of spec.connections)if(e.label)assert(measured.text.includes(e.label));
if(width===1440){
await page.setViewportSize({width:spec.meta.viewBox[0],height:spec.meta.viewBox[1]});
await page.screenshot({path:`${dir}/${topic}-standalone-export.png`});
}
results.push({topic,width,nodes:measured.nodes.length,edges:measured.edges.length,complete:true});await page.close();
}
fs.writeFileSync(`${dir}/export-results.json`,JSON.stringify(results,null,2));
console.log(`PASS ${results.length} standalone SVGs: exact graph, text, full-canvas containment and non-overlapping edge labels`);
}finally{await browser.close();}
})().catch(e=>{console.error(e);process.exitCode=1});
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const {chromium} = require('playwright');
const assert = require('node:assert/strict');
const fs = require('node:fs');
(async () => {
const base = process.argv[2] || 'http://127.0.0.1:4173';
const output = `.cache/measurement-${process.argv[3] || 'local'}`;
fs.mkdirSync(output, {recursive:true});
const browser = await chromium.launch({headless:true, executablePath:process.env.PLAYWRIGHT_CHROMIUM_EXECUTABLE, args:['--no-sandbox']});
const results = [];
try {
for (const width of [1440, 390, 320]) {
const context = await browser.newContext({viewport:{width,height:1000}, colorScheme:'light'});
const page = await context.newPage();
const errors = [];
page.on('pageerror', error => errors.push(error.message));
const response = await page.goto(`${base}/eldorado-v1/documentation/strategy/measurement/`, {waitUntil:'networkidle'});
assert.equal(response.status(), 200);
assert.equal(await page.locator('h1').innerText(), 'Skills Measurement');
assert((await page.title()).startsWith('Skills Measurement |'));
assert.equal(await page.locator('.strategy-content details').count(), 0);
assert.equal(await page.locator('.strategy-content h2').count(), 2);
assert.deepEqual((await page.locator('.strategy-content h3').allTextContents()).map(text => text.replaceAll('\u200b', '')), ['Workflow effectiveness', 'Skills effectiveness & health']);
assert.equal(await page.locator('.strategy-content ol').count(), 2);
assert.equal(await page.locator('.strategy-content ol > li').count(), 16);
if (width < 700) await page.getByRole('button', {name:'Toggle navigation bar'}).click();
const menu = page.locator('.theme-doc-sidebar-menu .menu__link').filter({visible:true});
await menu.first().waitFor({state:'visible'});
const metrics = JSON.parse(fs.readFileSync('research/ai-adoption/measurement-migration.json','utf8')).metrics;
assert.deepEqual(await menu.allTextContents(), ['Target','Roadmap','Stage - 01 - Skills Adoption','Measurement',...metrics.map(m => m.title),'Collection and safeguards','Run the synthetic measurement example','Baseline','Governance','Quality','Adoption','Maintenance','Stage - 02 - Autonomous Agent']);
if (width < 700) await page.getByRole('button', {name:'Close navigation bar'}).click();
const panel = page.locator('.archify-panel--story');
const iframe = panel.locator(width > 700 ? '.story-desktop' : '.story-mobile');
await iframe.scrollIntoViewIfNeeded();
const frame = await (await iframe.elementHandle()).contentFrame();
await frame.locator('svg[role="img"]').waitFor();
const geometry = await frame.locator('svg[role="img"]').evaluate(svg => {
const nodes = [...svg.querySelectorAll('[data-node-id]')].map(n => n.getBoundingClientRect().toJSON());
return {nodes, width:innerWidth, height:innerHeight, minLabel:Math.min(...[...svg.querySelectorAll('text[data-node-label]')].map(n => parseFloat(getComputedStyle(n).fontSize)*n.getScreenCTM().a))};
});
assert.equal(geometry.nodes.length, JSON.parse(fs.readFileSync('diagrams/strategy-measurement.architecture.json')).components.length);
for (const n of geometry.nodes) assert(n.x >= 0 && n.y >= 0 && n.right <= geometry.width + 1 && n.bottom <= geometry.height + 1);
assert(geometry.minLabel >= 10, `readable node labels: ${geometry.minLabel}`);
await frame.locator('#btn-theme').click();
await page.waitForFunction(() => document.documentElement.dataset.theme === 'dark');
await frame.locator('#btn-theme').click();
await page.waitForFunction(() => document.documentElement.dataset.theme === 'light');
for (const preset of ['signal-flow','blueprint','editorial','classic']) {
await frame.locator('#btn-preset').click();
await frame.locator(`[data-preset-value="${preset}"]`).click();
assert.equal(await frame.locator('html').getAttribute('data-preset'), preset);
}
await frame.locator('#btn-export').click();
const [download] = await Promise.all([page.waitForEvent('download'), frame.locator('[data-format="svg"]').click()]);
assert.equal(await download.failure(), null);
const path = `${output}/${width}.svg`; await download.saveAs(path);
const svg = fs.readFileSync(path, 'utf8');
assert(svg.includes('Workflow effectiveness') && svg.includes('Skills effectiveness &amp; health') && svg.includes('No mandatory collection'));
const exports = ['svg'];
for (const format of ['png','jpeg','webp','svg-light','svg-dark','webm']) {
await frame.locator('#btn-export').click();
const option = frame.locator(`[data-format="${format}"]`);
if (await option.isDisabled()) { exports.push(`${format}:unsupported`); await frame.locator('#btn-export').click(); continue; }
const [file] = await Promise.all([page.waitForEvent('download', {timeout:60000}), option.click()]);
assert.equal(await file.failure(), null);
const target = `${output}/${width}-${format}-${file.suggestedFilename()}`;
await file.saveAs(target);
const bytes = fs.readFileSync(target); assert(bytes.length > 1000);
if (format.startsWith('svg')) assert(bytes.toString().includes('eldorado-skills-typography'));
else {
const mime = {png:'image/png', jpeg:'image/jpeg', webp:'image/webp', webm:'video/webm'}[format];
const dimensions = await page.evaluate(async ({mime,data}) => {
const media = document.createElement(mime.startsWith('video') ? 'video' : 'img');
const ready = new Promise((resolve,reject) => {media[mime.startsWith('video') ? 'onloadedmetadata' : 'onload'] = resolve; media.onerror = reject;});
media.src = `data:${mime};base64,${data}`; await ready;
return [media.videoWidth || media.naturalWidth, media.videoHeight || media.naturalHeight];
}, {mime, data:bytes.toString('base64')});
assert(dimensions.every(n => n > 0));
}
exports.push(format);
}
const opener = panel.getByRole('button', {name:/^Expand /});
await opener.click();
const close = panel.getByRole('button', {name:'Close full-screen diagram', exact:true});
await close.waitFor({state:'visible'}); assert.equal(await close.innerText(), '×');
await close.click(); assert(await opener.evaluate(n => n === document.activeElement));
await opener.click(); await close.waitFor({state:'visible'}); await close.focus(); await page.keyboard.press('Escape');
await page.waitForFunction(() => !document.querySelector('.archify-panel--story dialog').open);
assert(await opener.evaluate(n => n === document.activeElement));
assert(!await page.evaluate(() => document.documentElement.scrollWidth > innerWidth));
await page.evaluate(() => scrollTo({top:0, behavior:'instant'}));
await page.screenshot({path:`${output}/${width}-top.png`});
await page.locator('.strategy-content h2').nth(1).scrollIntoViewIfNeeded();
await page.screenshot({path:`${output}/${width}-pilot.png`});
await page.screenshot({path:`${output}/${width}-full.png`, fullPage:true});
const links = await page.locator('.strategy-content a[href*="/measurement/"]').evaluateAll(nodes => nodes.map(n => n.href));
for (const href of [...new Set(links)]) {
const navigation = await page.goto(href, {waitUntil:'networkidle'});
if (navigation) assert.equal(navigation.status(), 200);
assert.equal(page.url(), href);
if (new URL(href).hash) await page.locator(new URL(href).hash).waitFor({state:'visible'});
}
assert.equal(new Set(links.map(h => new URL(h).pathname)).size, 18);
assert(!await page.evaluate(() => document.documentElement.scrollWidth > innerWidth));
assert.deepEqual(errors, []);
results.push({width, geometry, links:links.length, title:true, sidebar:true, controls:true, exports, reference:true});
fs.writeFileSync(`${output}/results.json`, JSON.stringify(results,null,2));
await context.close();
}
console.log(`PASS ${results.length} Skills Measurement viewports: title/sidebar, optional registry, diagram geometry/controls/export, all reference links and no page errors`);
} finally {await browser.close();}
})().catch(error => {console.error(error); process.exitCode = 1;});
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const {chromium}=require('playwright');
const fs=require('node:fs');
const assert=require('node:assert/strict');
(async()=>{
const base=process.argv[2]||'http://127.0.0.1:4173';
const out=`.cache/skills-${process.argv[3]||'candidate'}`;fs.mkdirSync(out,{recursive:true});
const browser=await chromium.launch({executablePath:process.env.PLAYWRIGHT_CHROMIUM_EXECUTABLE,args:['--no-sandbox']}); const results=[];
try {
for(const topic of ['measurement','baseline','governance','quality','adoption','maintenance']) for(const width of [1440,1024,390,320]) {
console.log(`Checking ${topic} at ${width}px`);
const page=await browser.newPage({viewport:{width,height:900},colorScheme:'light'});const errors=[];page.on('pageerror',e=>errors.push(e.message));
const route=['measurement','baseline'].includes(topic)?topic:`skills-${topic}`;
assert.equal((await page.goto(`${base}/eldorado-v1/documentation/strategy/${route}/`,{waitUntil:'networkidle'})).status(),200);
const panel=page.locator('.archify-panel--skills');assert.equal(await panel.count(),1);
const iframe=panel.locator(width>1100?'.story-desktop':'.story-mobile');await iframe.scrollIntoViewIfNeeded();
const frame=await(await iframe.elementHandle()).contentFrame();await frame.locator('svg[role="img"]').waitFor();
// Keep iframe controls below the fixed portal header. Frame-local click
// actionability cannot detect an overlay in the parent document.
const showControls=async()=>{
await panel.locator('dialog iframe').waitFor({state:'detached'});
await panel.evaluate(n=>{
scrollTo({top:n.getBoundingClientRect().top+scrollY-100,behavior:'instant'});
return new Promise(resolve=>requestAnimationFrame(()=>requestAnimationFrame(resolve)));
});
};
const geometry=await frame.locator('svg[role="img"]').evaluate(svg=>{
const nodes=[...svg.querySelectorAll('g[data-node-id]')];const issues=[];let min=Infinity;
for(const n of nodes){const rect=n.querySelector('rect').getBBox();for(const t of n.querySelectorAll('text')){
const b=t.getBBox();min=Math.min(min,parseFloat(getComputedStyle(t).fontSize)*t.getScreenCTM().a);
if(b.x<rect.x||b.y<rect.y||b.x+b.width>rect.x+rect.width||b.y+b.height>rect.y+rect.height)issues.push(n.id+':'+t.textContent);
}}
return {nodes:nodes.length,min,issues,width:innerWidth,svgWidth:svg.getBoundingClientRect().width};
});
const source=JSON.parse(fs.readFileSync(`diagrams/strategy-${topic}.architecture.json`));
assert.equal(geometry.nodes,source.components.length);assert.deepEqual(geometry.issues,[]);assert(geometry.min>=10,JSON.stringify(geometry));
for(const theme of ['light','dark']){
await showControls();
if(await frame.locator('html').getAttribute('data-theme')!==theme)await frame.locator('#btn-theme').click();
await page.waitForFunction(t=>document.documentElement.dataset.theme===t,theme).catch(error=>{throw new Error(`${topic}/${width}/${theme}: theme synchronization failed`,{cause:error});});
await panel.scrollIntoViewIfNeeded();await page.screenshot({path:`${out}/${topic}-${width}-${theme}-inline.png`});
const open=panel.getByRole('button',{name:/^Expand /});await open.click();const close=panel.getByRole('button',{name:'Close full-screen diagram',exact:true});await close.waitFor({state:'visible'});
const expanded=await(await panel.locator('dialog iframe').elementHandle()).contentFrame();await expanded.locator('svg[role="img"]').waitFor();
await expanded.waitForFunction(t=>document.documentElement.dataset.theme===t,theme);
await panel.locator('dialog').evaluate(n=>n.scrollTop=0);
assert((await expanded.url()).includes(width<=1100?`${topic}-mobile/`:`${topic}/`));
await page.screenshot({path:`${out}/${topic}-${width}-${theme}-fullscreen.png`});
if(width<=700){await page.setViewportSize({width,height:480});assert(await panel.locator('dialog').evaluate(n=>n.scrollHeight>n.clientHeight));await panel.locator('dialog').evaluate(n=>n.scrollTop=n.scrollHeight);await page.screenshot({path:`${out}/${topic}-${width}-${theme}-short-bottom.png`});await page.setViewportSize({width,height:900});}
await close.focus();await page.keyboard.press('Escape');assert(await open.evaluate(n=>n===document.activeElement));
}
await showControls();
await frame.locator('#btn-preset').click();await frame.locator('[data-preset-value="blueprint"]').click();
await frame.locator('#btn-preset').click();await frame.locator('[data-preset-value="classic"]').click();
await frame.locator('#btn-export').click();const [download]=await Promise.all([page.waitForEvent('download'),frame.locator('[data-format="svg"]').click()]);assert.equal(await download.failure(),null);
await download.saveAs(`${out}/${topic}-${width}.svg`);assert(fs.readFileSync(`${out}/${topic}-${width}.svg`,'utf8').includes('eldorado-skills-typography'));
assert(!await page.evaluate(()=>document.documentElement.scrollWidth>innerWidth));assert.deepEqual(errors,[]);
results.push({topic,width,geometry,controls:true,export:true,themes:true,fullscreen:true});fs.writeFileSync(`${out}/results.json`,JSON.stringify(results,null,2));await page.close();
}
console.log(`PASS ${results.length} Skills story contexts: geometry, themes, controls, exports, fullscreen and short-phone scrolling`);
}finally{await browser.close();}
})().catch(e=>{console.error(e);process.exitCode=1});
+95
View File
@@ -0,0 +1,95 @@
const {chromium} = require('playwright');
const assert = require('node:assert/strict');
const fs = require('node:fs');
(async () => {
const base = process.argv[2] || 'http://127.0.0.1:4173';
const output = `.cache/strategy-navigation-${process.argv[3] || 'local'}`;
fs.mkdirSync(output, {recursive:true});
const prefix = '/eldorado-v1/documentation/strategy/';
const first = 'Stage - 01 - Skills Adoption';
const second = 'Stage - 02 - Autonomous Agent';
const topics = ['Measurement','Baseline','Governance','Quality','Adoption','Maintenance'];
const metrics = JSON.parse(fs.readFileSync('research/ai-adoption/measurement-migration.json','utf8')).metrics;
const childIds = [...metrics.map(m => m.docId),'measurement/collection-and-safeguards','measurement/synthetic-example'];
const childTitles = [...metrics.map(m => m.title),'Collection and safeguards','Run the synthetic measurement example'];
const ids = ['target-operating-model','roadmap','stage-01-skills-adoption','measurement',...childIds,'baseline','skills-governance','skills-quality','skills-adoption','skills-maintenance','stage-02-autonomous-agent'];
const titles = ['Target','Roadmap',first,'Skills Measurement',...childTitles,'Baseline','Skills governance','Skills quality','Skills adoption','Skills maintenance',second];
const browser = await chromium.launch({headless:true, executablePath:process.env.PLAYWRIGHT_CHROMIUM_EXECUTABLE, args:['--no-sandbox']});
const results = [];
try {
for (const width of [1440,1024,390,320]) {
const context = await browser.newContext({viewport:{width,height:900}, colorScheme:'light'});
try {
const page = await context.newPage();
const errors = [];
page.on('pageerror', error => errors.push(error.message));
const openMenu = async () => {
if (width < 997) await page.getByRole('button', {name:'Toggle navigation bar'}).click();
const menu = page.locator('.theme-doc-sidebar-menu').filter({visible:true});
await menu.locator('.menu__link').first().waitFor({state:'visible'});
return menu;
};
const closeMenu = async () => {
if (width < 997) await page.getByRole('button', {name:'Close navigation bar'}).click();
};
assert.equal((await page.goto(`${base}${prefix}roadmap/`, {waitUntil:'networkidle'})).status(), 200);
let menu = await openMenu();
const visibleLabels = () => menu.locator('.menu__link').filter({visible:true}).allTextContents();
assert.deepEqual(await visibleLabels(), ['Target','Roadmap',first,second]);
const category = menu.locator('.theme-doc-sidebar-item-category').filter({has:page.getByRole('link', {name:first, exact:true})});
const caret = category.locator(':scope > .menu__list-item-collapsible > button.menu__caret');
await caret.click();
await category.getByRole('link', {name:'Governance', exact:true}).waitFor({state:'visible'});
assert.deepEqual(await visibleLabels(), ['Target','Roadmap',first,...topics,second]);
assert.deepEqual(await category.locator('ul .menu__link').filter({visible:true}).allTextContents(), topics);
const measurement = category.locator('.theme-doc-sidebar-item-category').filter({has:page.getByRole('link', {name:'Measurement', exact:true})});
const reference = measurement.locator(':scope > .menu__list-item-collapsible > button.menu__caret');
await reference.focus();
await page.keyboard.press('Enter');
await category.getByRole('link', {name:'Validated task success', exact:true}).waitFor({state:'visible'});
assert.deepEqual(await visibleLabels(), ['Target','Roadmap',first,topics[0],...childTitles,...topics.slice(1),second]);
await reference.click();
await page.screenshot({path:`${output}/${width}-expanded.png`, animations:'disabled'});
await caret.click();
await category.getByRole('link', {name:'Governance', exact:true}).waitFor({state:'hidden'});
assert.deepEqual(await visibleLabels(), ['Target','Roadmap',first,second]);
await menu.getByRole('link', {name:first, exact:true}).click();
await page.waitForURL(`${base}${prefix}stage-01-skills-adoption/`);
await page.getByRole('heading', {level:1, name:first, exact:true}).waitFor();
assert.equal(await page.locator('h1').innerText(), first);
assert((await page.locator('article').innerText()).includes('Delivery first'));
assert(!await page.evaluate(() => document.documentElement.scrollWidth > innerWidth));
await page.screenshot({path:`${output}/${width}-stage-01.png`, fullPage:true, animations:'disabled'});
for (const [index, id] of ids.entries()) {
assert.equal((await page.goto(`${base}${prefix}${id}/`, {waitUntil:'networkidle'})).status(), 200);
assert.equal(new URL(page.url()).pathname, `${prefix}${id}/`);
// Target has a longer canonical page heading but keeps its short navigation label.
if (index) assert.equal(await page.locator('h1').innerText(), titles[index]);
else assert((await page.locator('h1').innerText()).includes('Target'));
const prev = page.locator('.pagination-nav__link--prev');
const next = page.locator('.pagination-nav__link--next');
if (index) assert.equal(await prev.getAttribute('href'), `${prefix}${id === 'baseline' ? 'measurement' : ids[index-1]}/`);
else assert.equal(await prev.count(), 0);
if (index < ids.length-1) assert.equal(await next.getAttribute('href'), `${prefix}${id === 'measurement' ? 'baseline' : ids[index+1]}/`);
else assert.equal(await next.count(), 0);
if (index >= 3 && index < ids.length - 1) {
assert.equal(await page.locator('.breadcrumbs a').filter({hasText:first}).getAttribute('href'), `${prefix}stage-01-skills-adoption/`);
menu = await openMenu();
const expectedTopics = id === 'measurement' || id.startsWith('measurement/') ? [topics[0],...childTitles,...topics.slice(1)] : topics;
assert.deepEqual(await visibleLabels(), ['Target','Roadmap',first,...expectedTopics,second]);
if (id.startsWith('measurement/')) assert.equal(await page.locator('.breadcrumbs a').filter({hasText:'Measurement'}).getAttribute('href'), `${prefix}measurement/`);
await closeMenu();
}
assert(!await page.evaluate(() => document.documentElement.scrollWidth > innerWidth), `${width}: overflow on ${id}`);
}
assert((await page.locator('article').innerText()).includes('not deployed autonomy'));
await page.screenshot({path:`${output}/${width}-stage-02.png`, fullPage:true, animations:'disabled'});
assert.deepEqual(errors, []);
results.push({width, routes:ids.length, linkedCategory:true, expandCollapse:true, nesting:true, breadcrumbs:true, pagination:true, overflow:false, errors});
fs.writeFileSync(`${output}/results.json`, JSON.stringify(results,null,2));
} finally {await context.close();}
}
assert.equal(results.length, 4);
console.log(`PASS: 4 desktop/mobile viewports; all ${ids.length} routes; linked Measurement category, keyboard expansion, breadcrumbs, next/previous and no overflow/errors`);
} finally {await browser.close();}
})().catch(error => {console.error(error); process.exitCode = 1;});
+22 -11
View File
@@ -12,30 +12,41 @@ const fs=require('node:fs');
const page=await context.newPage();
for(const id of ['index','target-operating-model','skills-governance','skills-quality','skills-adoption','measurement','skills-maintenance','roadmap']){
const response=await page.goto(`${base}/eldorado-v1/documentation/strategy/${id==='index'?'':id+'/'}`,{waitUntil:'networkidle'});assert.equal(response.status(),200);
const panel=page.locator('.archify-panel--story');
const panel=page.locator('.archify-panel--story').first();
const iframe=panel.locator(width===390?'.story-mobile':'.story-desktop');await iframe.scrollIntoViewIfNeeded();
const frame=await (await iframe.elementHandle()).contentFrame();await frame.locator('svg[role="img"]').waitFor();
const geometry=await frame.locator('svg[role="img"]').evaluate(svg=>{
const nodes=[...svg.querySelectorAll('[data-node-id]')].map(n=>{const r=n.getBoundingClientRect();return {id:n.id,x:r.x,y:r.y,right:r.right,bottom:r.bottom};});
return {width:innerWidth,height:innerHeight,nodes,svg:svg.getBoundingClientRect().toJSON(),minLabel:Math.min(...[...svg.querySelectorAll('text[data-node-label]')].map(n=>parseFloat(getComputedStyle(n).fontSize)*n.getScreenCTM().a))};
});
assert(geometry.nodes.length>=5 && geometry.nodes.length<=7,id);
const name=await panel.getAttribute('data-diagram');
const source=JSON.parse(fs.readFileSync(`diagrams/${name}.${name==='strategy-roadmap'?'workflow':'architecture'}.json`));
assert.equal(geometry.nodes.length,(source.components||source.nodes).length,id);
for(const n of geometry.nodes) assert(n.x>=0 && n.y>=0 && n.right<=geometry.width+1 && n.bottom<=geometry.height+1,`${id} ${width} clipped ${JSON.stringify(n)} / ${geometry.height}`);
const data=await page.locator('.strategy-content').evaluate(el=>({words:el.innerText.trim().split(/\s+/).length,overflow:document.documentElement.scrollWidth>innerWidth,openDetails:el.querySelectorAll('details[open]').length}));
assert(data.words<=200,id);assert(!data.overflow,id);assert.equal(data.openDetails,0,id);
await page.evaluate(()=>scrollTo(0,0));await page.screenshot({path:`.cache/story-${label}/${width}-${id}.png`,fullPage:true});
assert(data.words<=(id==='measurement'?1500:id==='roadmap'?600:200),id);assert(!data.overflow,id);assert.equal(data.openDetails,0,id);
await page.evaluate(()=>scrollTo({top:0,behavior:'instant'}));await page.screenshot({path:`.cache/story-${label}/${width}-${id}.png`,fullPage:true});
const opener=panel.getByRole('button',{name:/^Expand /});await opener.click();
const close=panel.getByRole('button',{name:'Close full-screen diagram',exact:true});await close.waitFor({state:'visible'});
assert.equal(await close.innerText(),'×');assert(await close.evaluate(n=>n===document.activeElement));
const box=await close.boundingBox();assert.equal(box.width,44);assert.equal(box.height,44);
await close.click();assert(await opener.evaluate(n=>n===document.activeElement));
await opener.click();await close.waitFor({state:'visible'});await page.keyboard.press('Escape');await page.waitForFunction(()=>!document.querySelector('.archify-panel--story dialog').open);assert(await opener.evaluate(n=>n===document.activeElement));
const summary=page.locator('.strategy-content > details > summary').first();await summary.click();assert(await summary.evaluate(n=>n.parentElement.open));await summary.click();
results.push({id,width,...data,geometry,modalClick:true,modalEscape:true,focusRestored:true,details:true});fs.writeFileSync(`.cache/story-${label}/results.json`,JSON.stringify(results,null,2));
await close.click();await panel.locator('dialog iframe').waitFor({state:'detached'});assert(await opener.evaluate(n=>n===document.activeElement));
await opener.click();await close.waitFor({state:'visible'});await page.keyboard.press('Escape');await page.waitForFunction(()=>!document.querySelector('.archify-panel--story dialog').open);
// Native close clears open before the queued React onClose restores focus.
// Wait for its unmount before focusing the next keyboard interaction target.
await panel.locator('dialog iframe').waitFor({state:'detached'});assert(await opener.evaluate(n=>n===document.activeElement));
if(id !== 'measurement') {
const summary=page.locator('.strategy-content > details > summary').first();
await summary.focus();await page.keyboard.press('Enter');
await page.waitForFunction(()=>document.querySelector('.strategy-content > details').open);
await page.keyboard.press('Enter');
}
results.push({id,width,...data,geometry,modalClick:true,modalEscape:true,focusRestored:true,details:id!=='measurement'});fs.writeFileSync(`.cache/story-${label}/results.json`,JSON.stringify(results,null,2));
}
await page.goto(`${base}/eldorado-v1/documentation/strategy/measurement/#validated-task-success`,{waitUntil:'networkidle'});
const heading=page.locator('#validated-task-success');await heading.waitFor({state:'visible'});
assert(await heading.evaluate(n=>n.closest('details').open),'hash should open metric reference');
await page.goto(`${base}/eldorado-v1/documentation/strategy/reference/measurement-contracts/#validated-task-success`,{waitUntil:'networkidle'});
await page.waitForURL(`${base}/eldorado-v1/documentation/strategy/measurement/validated-task-success/`);
await page.getByRole('heading',{level:1,name:'Validated task success',exact:true}).waitFor();
assert.equal(await page.locator('.strategy-content details').count(),0,'reference is directly readable');
await context.close();
}
console.log(`PASS ${results.length} desktop/mobile cases, clipping, default word count, details, modal click/Escape/focus and KPI hash navigation`);
+185
View File
@@ -0,0 +1,185 @@
const {chromium} = require('playwright');
const assert = require('node:assert/strict');
const fs = require('node:fs');
const {pathToFileURL} = require('node:url');
const {resolve} = require('node:path');
// Inspect the rendered paths, not just the authored JSON. Also runs on downloaded SVGs.
function inspect({mobile}) {
const svg = document.querySelector('svg[role="img"]');
const point = (element, p) => new DOMPoint(p.x, p.y).matrixTransform(element.getCTM());
const boxes = [...svg.querySelectorAll('[data-node-id]')].map(node => {
const rect = node.querySelector('rect'), box = rect.getBBox();
const a = point(rect, box), b = point(rect, {x:box.x + box.width, y:box.y + box.height});
return {id:node.dataset.nodeId, x:a.x, y:a.y, right:b.x, bottom:b.y, cx:(a.x+b.x)/2, cy:(a.y+b.y)/2};
});
const agent = boxes.find(n => n.id === 'agent');
const errors = [], endpoints = {};
const phases = ['scope','architecture','ui-ux','planning','delivery','uat','security','releases'];
const edges = [...svg.querySelectorAll('path[data-edge-id]')];
if (edges.length !== 24) errors.push(`expected 24 graph edges, got ${edges.length}`);
phases.forEach((phase, index) => {
for (const [id, from, to] of [
[`govern-${phase}`,'agent',phase],
[`stage-${index+1}`,phase,phases[(index+1)%phases.length]],
[`contribute-${phase}`,`code-${phase}`,phase],
]) {
const matches = edges.filter(p => p.dataset.edgeId === id);
if (matches.length !== 1 || matches[0].dataset.edgeFrom !== from || matches[0].dataset.edgeTo !== to || !matches[0].getAttribute('marker-end') || matches[0].getAttribute('marker-start')) errors.push(`${id}: graph or direction changed`);
}
});
// CTMs put boxes and paths in the same viewport coordinate system.
// 0.01 covers floating-point error against bounds, NOT source spreading:
// shared endpoints below must be exactly identical.
const paths = [...svg.querySelectorAll('path[data-edge-id^="govern-"]')];
if (paths.length !== 8) errors.push(`expected eight governance paths, got ${paths.length}`);
for (const path of paths) {
const id = path.dataset.edgeTo;
const side = mobile ? 'left' : ['scope','architecture','releases'].includes(id) ? 'top'
: ['planning','delivery','uat'].includes(id) ? 'bottom' : id === 'security' ? 'left' : 'right';
const expected = {top:[agent.cx,agent.y],bottom:[agent.cx,agent.bottom],left:[agent.x,agent.cy],right:[agent.right,agent.cy]}[side];
const start = point(path,path.getPointAtLength(0));
endpoints[id] = [start.x,start.y];
if (Math.hypot(start.x-expected[0],start.y-expected[1]) > 0.01) errors.push(`${id}: wrong ${side} midpoint`);
const length = path.getTotalLength();
const target = boxes.find(n => n.id === id);
const destination = mobile ? [target.x,target.cy]
: side === 'top' ? [target.cx,target.bottom] : side === 'bottom' ? [target.cx,target.y]
: side === 'left' ? [target.right,target.cy] : [target.x,target.cy];
const end = point(path,path.getPointAtLength(length));
if (Math.hypot(end.x-destination[0],end.y-destination[1]) > 0.01) errors.push(`${id}: destination midpoint changed`);
for (let distance = 1; distance < length; distance += 2) {
const p = point(path,path.getPointAtLength(distance));
for (const box of boxes) {
if (box.id === id) continue;
if (p.x > box.x+0.1 && p.x < box.right-0.1 && p.y > box.y+0.1 && p.y < box.bottom-0.1) {
errors.push(`${id}: crosses ${box.id}`); break;
}
}
}
}
for (const group of mobile ? [phases] : [['scope','architecture','releases'],['planning','delivery','uat']]) {
const first = endpoints[group[0]];
if (group.some(id => !endpoints[id] || endpoints[id][0] !== first?.[0] || endpoints[id][1] !== first?.[1])) errors.push(`source-port spreading: ${group.join(',')}`);
}
const lifecycle = [];
if (!mobile) {
for (const [id, x, y1, y2, peer] of [
['stage-2',850,262.5,457.5,'architecture'], ['stage-3',850,532.5,727.5,'planning'],
['stage-6',350,727.5,532.5,'uat'], ['stage-7',350,457.5,262.5,'releases'],
]) {
const path = svg.querySelector(`path[data-edge-id="${id}"]`);
if (!path) {errors.push(`${id}: missing lifecycle path`); continue;}
const length = path.getTotalLength();
const a = path.getPointAtLength(0), b = path.getPointAtLength(length);
// Local SVG coordinates test exact offsets; transformed coordinates test
// node clearance at any inline/fullscreen/export scale.
if (Math.hypot(a.x-x,a.y-y1) > 0.01 || Math.hypot(b.x-x,b.y-y2) > 0.01) errors.push(`${id}: wrong shifted endpoints`);
if (!path.getAttribute('marker-end')) errors.push(`${id}: missing direction`);
const governance = paths.find(p => p.dataset.edgeTo === peer);
if (!governance) {errors.push(`${id}: missing governance peer ${peer}`); continue;}
const end = governance.getPointAtLength(governance.getTotalLength());
if (Math.abs(Math.abs(a.x-end.x)-20) > 0.01) errors.push(`${id}: wrong attachment clearance`);
for (let distance = 1; distance < length; distance += 2) {
const local = path.getPointAtLength(distance), p = point(path,local);
if (Math.abs(local.x-x) > 0.01) errors.push(`${id}: channel not straight`);
for (const box of boxes) {
if (p.x > box.x+0.1 && p.x < box.right-0.1 && p.y > box.y+0.1 && p.y < box.bottom-0.1) errors.push(`${id}: crosses ${box.id}`);
}
}
// No positive-length collinear overlap with ANY governance segment.
// Perpendicular crossings remain legitimate in this fixed radial layout.
for (const govern of paths) {
const total = govern.getTotalLength();
for (let d = 0; d < total - 1; d += 1) {
const p = govern.getPointAtLength(d), q = govern.getPointAtLength(d+1);
if (Math.abs(p.x-x) < 0.01 && Math.abs(q.x-x) < 0.01 && Math.min(Math.max(p.y,q.y),Math.max(y1,y2)) - Math.max(Math.min(p.y,q.y),Math.min(y1,y2)) > 0.01) errors.push(`${id}: overlaps ${govern.dataset.edgeId}`);
}
}
lifecycle.push({id,start:[a.x,a.y],end:[b.x,b.y],attachmentClearance:Math.abs(a.x-end.x)});
}
}
return {errors:[...new Set(errors)],endpoints,lifecycle};
}
function inspectTypography({mobile}) {
const errors = [];
const nodes = [...document.querySelectorAll('[data-node-id]')].map(node => {
const box = node.querySelector('rect').getBoundingClientRect();
const texts = [...node.querySelectorAll(':scope > text')];
const bounds = texts.map(text => text.getBoundingClientRect());
texts.forEach((text, index) => {
const expected = text.hasAttribute('data-node-label') ? (mobile ? 38 : 27) : (mobile ? 28 : 21);
if (parseFloat(getComputedStyle(text).fontSize) !== expected) errors.push(`${node.id}: wrong text size`);
const b = bounds[index];
if (b.width <= 0 || b.height <= 0 || b.x < box.x - 1 || b.right > box.right + 1 || b.y < box.y - 1 || b.bottom > box.bottom + 1) errors.push(`${node.id}: text outside node`);
});
if (bounds.length === 2 && bounds[0].bottom > bounds[1].top) errors.push(`${node.id}: title/subtitle overlap`);
return {id:node.id, text:texts.map(t => t.textContent), sizes:texts.map(t => getComputedStyle(t).fontSize)};
});
if (nodes.length !== 17) errors.push(`expected 17 nodes, got ${nodes.length}`);
return {errors, nodes};
}
(async () => {
const base = process.argv[2] || 'http://127.0.0.1:4173';
const output = `.cache/midpoints-${process.argv[3] || 'local'}`;
fs.mkdirSync(output,{recursive:true});
const browser = await chromium.launch({headless:true, executablePath:process.env.PLAYWRIGHT_CHROMIUM_EXECUTABLE,args:['--no-sandbox']});
const results = [];
try {
for (const width of [1440,390,320]) {
const page = await browser.newPage({viewport:{width,height:1000}});
await page.goto(`${base}/eldorado-v1/documentation/strategy/target-operating-model/`,{waitUntil:'networkidle'});
const panel = page.locator('[data-diagram="strategy-target"]');
const iframe = panel.locator(`:scope > .story-${width > 700 ? 'desktop' : 'mobile'}`);
await iframe.scrollIntoViewIfNeeded();
const frame = await (await iframe.elementHandle()).contentFrame();
await frame.locator('svg[role="img"]').waitFor();
const inline = await frame.evaluate(inspect,{mobile:width < 700});
assert.deepEqual(inline.errors,[]);
await page.screenshot({path:`${output}/${width}-inline.png`,fullPage:true});
const exported = [];
for (const theme of ['light','dark']) {
if (await frame.locator('html').getAttribute('data-theme') !== theme) await frame.locator('#btn-theme').click();
await frame.waitForFunction(t => document.documentElement.dataset.theme === t, theme);
await frame.locator('#btn-export').click();
const [download] = await Promise.all([page.waitForEvent('download'),frame.locator('[data-format="svg"]').click()]);
assert.equal(await download.failure(),null);
const path = `${output}/${width}-${theme}.svg`;
await download.saveAs(path);
// A separate SVG document has no viewer CSS to hide export regressions.
const standalone = await browser.newPage({viewport:{width:1440,height:1100},colorScheme:theme});
await standalone.goto(pathToFileURL(resolve(path)).href);
assert.equal(await standalone.evaluate(() => document.contentType),'image/svg+xml');
await standalone.evaluate(() => document.fonts.ready);
const geometry = await standalone.evaluate(inspect,{mobile:width < 700});
const typography = await standalone.evaluate(inspectTypography,{mobile:width < 700});
assert.deepEqual(geometry.errors,[]);
assert.deepEqual(typography.errors,[]);
const background = await standalone.locator('rect.c-bg-rect').evaluate(n => getComputedStyle(n).fill);
if (exported.length) assert.notEqual(background,exported[0].background,'standalone theme must change');
// CDP captures SVG documents without Playwright's HTML-body screenshot wait.
const client = await standalone.context().newCDPSession(standalone);
const size = await standalone.evaluate(() => ({width:document.documentElement.width.baseVal.value,height:document.documentElement.height.baseVal.value}));
const image = await client.send('Page.captureScreenshot',{format:'png',captureBeyondViewport:true,clip:{x:0,y:0,...size,scale:1}});
fs.writeFileSync(`${output}/${width}-${theme}-standalone.png`,Buffer.from(image.data,'base64'));
exported.push({theme,background,geometry,typography});
await standalone.close();
}
await panel.getByRole('button',{name:/^Expand /}).click();
const full = await (await panel.locator('dialog iframe').elementHandle()).contentFrame();
await full.locator('svg[role="img"]').waitFor();
// The existing fullscreen viewer always opens the radial desktop source.
const fullscreen = await full.evaluate(inspect,{mobile:false});
assert.deepEqual(fullscreen.errors,[]);
await page.screenshot({path:`${output}/${width}-fullscreen.png`});
await panel.getByRole('button',{name:'Close full-screen diagram'}).click();
results.push({width,inline,exported,fullscreen});
fs.writeFileSync(`${output}/results.json`,JSON.stringify(results,null,2));
await page.close();
}
assert.equal(results.length,3);
console.log('PASS midpoint geometry: 3 viewports × inline/fullscreen; standalone SVG geometry and typography in light/dark');
} finally {await browser.close();}
})().catch(error => {console.error(error);process.exitCode=1;});
+46 -5
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@@ -1,9 +1,14 @@
import {readdirSync, readFileSync, writeFileSync, mkdirSync, copyFileSync, renameSync, rmSync} from 'node:fs';
import {join} from 'node:path';
import {execFileSync} from 'node:child_process';
import {skillsViewer, isSkillsStory} from './skills-viewer.mjs';
import {roadmapViewer} from './roadmap-viewer.mjs';
import {targetRouting} from './target-routing.mjs';
import {createHash} from 'node:crypto';
const cli = 'vendor/archify/bin/archify.mjs';
const types = new Set(['architecture','workflow','sequence','dataflow','lifecycle']);
const inlineStyles = readFileSync(new URL('./inline-viewer.css', import.meta.url), 'utf8');
const cycleStyles = readFileSync(new URL('./cycle-viewer.css', import.meta.url), 'utf8');
const themeBridge = readFileSync(new URL('./viewer-theme-bridge.js', import.meta.url), 'utf8');
// This directory is generated-only and ignored by Git. Remove stale artifacts.
rmSync('static/diagrams', {recursive: true, force: true});
@@ -22,11 +27,22 @@ for (const file of readdirSync('diagrams').sort()) {
mkdirSync(`static/diagrams/${name}`, {recursive: true});
if (spec.diagram_type !== type || spec.meta.output !== output) throw new Error(`Diagram type/output mismatch: ${file}`);
const run = args => execFileSync(process.execPath,[cli,...args],{stdio:'inherit',env:{...process.env,ARCHIFY_UPDATE_CHECK_DISABLED:'1'}});
run(['validate',type,input,'--quality','showcase','--json']);
run(['deliver',type,input,output,'--quality','showcase','--json']);
run(['check',output,'--json','--require-provenance']);
const roadmap = /^strategy-roadmap(?:-(?:adoption|loop))?(?:-mobile)?$/.test(name);
const skills = isSkillsStory(name);
if (roadmap || skills) {
// Native renderer validates schema and compiles layout. Check readability
// after multiline typography, not upstream's single-line preview.
execFileSync(process.execPath, [`vendor/archify/renderers/${type}/render-${type}.mjs`, input, output], {stdio:'inherit', env:{...process.env, ARCHIFY_UPDATE_CHECK_DISABLED:'1'}});
writeFileSync(output, (skills ? skillsViewer : roadmapViewer)(readFileSync(output, 'utf8'), spec));
run(['check',output,'--json']);
} else {
run(['validate',type,input,'--quality','showcase','--json']);
run(['deliver',type,input,output,'--quality','showcase','--json']);
run(['check',output,'--json','--require-provenance']);
}
// Verify the upstream artifact first, then add the scoped portal integration.
let viewer = readFileSync(output, 'utf8');
if (name === 'strategy-target') viewer = targetRouting(viewer);
// Upstream intentionally disables preset selection in gallery embeds. Enable
// only those two guards; fail closed if a future vendor update changes them.
const start = viewer.indexOf('Archify.preset = (function () {');
@@ -36,9 +52,34 @@ for (const file of readdirSync('diagrams').sort()) {
if (start < 0 || end < start || preset.split(guard).length !== 3) throw new Error('Archify preset integration drift');
viewer = viewer.slice(0, start) + preset.replaceAll(guard, '') + viewer.slice(end);
if (!viewer.includes('</head>') || !viewer.includes('</body>')) throw new Error(`Invalid viewer: ${output}`);
writeFileSync(output, viewer.replace('</head>', `<style id="eldorado-inline-controls">${inlineStyles}</style></head>`)
const storyStyles = ['strategy-target', 'strategy-target-mobile'].includes(name)
? `${name === 'strategy-target' ? ':root {--cycle-label: 27px; --cycle-detail: 21px;}' : ':root {--cycle-label: 38px; --cycle-detail: 28px;}'}${cycleStyles}` : '';
if (storyStyles) {
// Keep typography and relationship styles inside exported standalone SVGs.
const diagramRoot = /<svg\b[^>]*role="img"[^>]*>/g;
if ([...viewer.matchAll(diagramRoot)].length !== 1) throw new Error('Cycle SVG integration drift');
const exportStyles = storyStyles.replaceAll(':root', 'svg[role="img"]').replaceAll('.diagram-container > svg', 'svg[role="img"]');
viewer = viewer.replace(diagramRoot, root => `${root}<style id="eldorado-cycle-export">${exportStyles}</style>`);
}
writeFileSync(output, viewer.replace('</head>', `<style id="eldorado-inline-controls">${inlineStyles}</style><style id="eldorado-cycle-labels">${storyStyles}</style></head>`)
.replace('</body>', `<script>${themeBridge}</script></body>`));
renameSync(`static/diagrams/${name}/index.delivery.json`, `.cache/archify/${name}.delivery.json`);
if (roadmap || skills) {
// This is a portal receipt, not upstream deliver provenance: formatting
// happens between the native schema/layout compiler and artifact checker.
const hash = path => createHash('sha256').update(readFileSync(path)).digest('hex');
const checked = JSON.parse(execFileSync(process.execPath, [cli,'check',output,'--json'], {encoding:'utf8', env:{...process.env, ARCHIFY_UPDATE_CHECK_DISABLED:'1'}}));
if (!checked.ok || checked.composition?.status !== 'pass') throw new Error('Story final artifact failed');
writeFileSync(`.cache/archify/${name}.portal.json`, JSON.stringify({source:input, sourceSha256:hash(input), adapterSha256:hash(skills ? 'scripts/skills-viewer.mjs' : 'scripts/roadmap-viewer.mjs'), artifactSha256:hash(output), checker:checked}, null, 2));
} else {
renameSync(`static/diagrams/${name}/index.delivery.json`, `.cache/archify/${name}.delivery.json`);
if (name === 'strategy-target') {
// The native receipt describes the PRE-integration artifact only.
const hash = path => createHash('sha256').update(readFileSync(path)).digest('hex');
const checked = JSON.parse(execFileSync(process.execPath, [cli,'check',output,'--json'], {encoding:'utf8', env:{...process.env, ARCHIFY_UPDATE_CHECK_DISABLED:'1'}}));
if (!checked.ok || checked.composition?.status !== 'pass') throw new Error('Target final artifact failed');
writeFileSync(`.cache/archify/${name}.portal.json`, JSON.stringify({source:input, sourceSha256:hash(input), adapterSha256:hash('scripts/target-routing.mjs'), artifactSha256:hash(output), nativeReceiptScope:'before portal integration', checker:checked}, null, 2));
}
}
}
copyFileSync('vendor/archify/LICENSE','static/diagrams/ARCHIFY-LICENSE.txt');
copyFileSync('vendor/archify/THIRD_PARTY_NOTICES.md','static/diagrams/THIRD-PARTY-NOTICES.md');
+20
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@@ -0,0 +1,20 @@
/* Readable lifecycle story at inline scale, isolated from other diagrams. */
.diagram-container > svg text {
font-family: Arial, sans-serif;
letter-spacing: 0;
font-size: 30px;
}
.diagram-container > svg text[data-node-label] {
font-size: var(--cycle-label);
transform: translateY(-6px);
}
/* Export strips data-detail; node ownership and the muted class survive. */
.diagram-container > svg [data-node-id] > text.t-muted {
font-size: var(--cycle-detail);
transform: translateY(16px);
}
/* Edge semantics stay in SVG metadata; one page legend avoids repeated labels. */
.diagram-container > svg g[data-edge-id] {display: none;}
.diagram-container > svg path[data-edge-id^="stage-"] {stroke-width: 2.5;}
.diagram-container > svg path[data-edge-id^="govern-"] {stroke-dasharray: 3 9; stroke-width: 3;}
.diagram-container > svg path[data-edge-id^="contribute-"] {stroke-dasharray: 12 8; stroke-width: 3;}
+38
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@@ -0,0 +1,38 @@
import assert from 'node:assert/strict';
import {readFileSync, readdirSync} from 'node:fs';
import {runInNewContext} from 'node:vm';
const read = p => readFileSync(p, 'utf8');
export function verifyMeasurementPages() {
const manifest = JSON.parse(read('research/ai-adoption/measurement-migration.json'));
const {documents, exclusions} = JSON.parse(read('.cache/sidebar-coverage.json'));
const prefix = '/eldorado-v1/documentation';
const legacy = 'strategy/reference/measurement-contracts/index.html';
assert.equal(exclusions.filter(e => e.file === legacy).length, 1);
assert(!documents.some(d => d.id === 'reference/measurement-contracts'));
const search = readdirSync('build').filter(f => /^search-index.*\.json$/.test(f)).map(f => read(`build/${f}`)).join('\n');
assert(!search.includes('/strategy/reference/measurement-contracts/'));
const children = [...manifest.metrics.map(m => ({...m,slug:m.oldAnchor})),
{slug:'collection-and-safeguards',title:'Collection and safeguards'},
{slug:'synthetic-example',title:'Run the synthetic measurement example'},
];
for (const child of children) {
const route = `${prefix}/strategy/measurement/${child.slug}/`;
const doc = documents.filter(d => `${d.route}/` === route);
assert.equal(doc.length,1);
assert.equal(doc[0].id, `measurement/${child.slug}`);
const page = read(`build/strategy/measurement/${child.slug}/index.html`);
const canonical = [...page.matchAll(/<link\b[^>]*rel="canonical"[^>]*>/g)];
assert.equal(canonical.length,1);
assert(canonical[0][0].includes(`href="https://pages.apps.lego-cloud.eu${route}"`));
assert(search.includes(route), `Missing search route: ${route}`);
assert(!page.includes(`${prefix}/strategy/reference/measurement-contracts/`));
}
const script = read(`build/${legacy}`).match(/<script>([\s\S]*?)<\/script>/)[1];
for (const m of manifest.metrics) {
let destination;
runInNewContext(script,{window:{location:{hash:`#${m.oldAnchor}`,replace:url => {destination=url;}}}});
assert.equal(destination,`${prefix}${m.url}`);
}
console.log('PASS: 18 canonical Measurement children, exact IDs, search membership and 16 hash redirects; no legacy document/index duplication');
}
+42
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@@ -0,0 +1,42 @@
import test from 'node:test';
import assert from 'node:assert/strict';
import {readFileSync, existsSync, readdirSync} from 'node:fs';
import {createHash} from 'node:crypto';
import {calculate} from './ai-kpi.mjs';
const read = p => readFileSync(p, 'utf8');
test('each original metric survives exactly once on its own canonical Measurement page', () => {
const manifest = JSON.parse(read('research/ai-adoption/measurement-migration.json'));
const model = JSON.parse(read('research/ai-adoption/strategy-model.json'));
const report = calculate(JSON.parse(read('scripts/fixtures/ai-kpi-synthetic.json')));
assert.equal(manifest.metrics.length, 16);
assert.deepEqual(manifest.metrics.map(m => m.title), model.kpis.map(k => k.name));
assert.equal(new Set(manifest.metrics.map(m => m.docId)).size, 16);
assert.equal(manifest.metrics.filter(m => m.status === 'prototype').length, 9);
assert.equal(manifest.metrics.filter(m => m.status === 'unimplemented').length, 7);
const overview = read('docs/strategy/measurement/index.mdx');
for (const metric of manifest.metrics) {
const page = read(`docs/strategy/${metric.docId}.mdx`);
assert.equal(metric.url, `/strategy/${metric.docId}/`);
assert.equal(metric.oldAnchor, metric.docId.split('/').at(-1));
assert(page.includes(`slug: /${metric.docId}`));
assert(overview.includes(`./${metric.oldAnchor}.mdx`));
assert(page.includes('./collection-and-safeguards.mdx'));
assert(page.includes('not installed collection'));
assert(page.includes(metric.status === 'prototype' ? 'Prototype calculation' : 'Unimplemented metric'));
assert.equal(Object.hasOwn(report.kpis, metric.calculationId), metric.status === 'prototype');
const contract = page.split('{/* contract:start */}\n')[1]?.split('\n{/* contract:end */}')[0];
assert(contract, metric.title);
assert.equal(createHash('sha256').update(contract).digest('hex'), metric.contractSha256, metric.title);
for (const field of ['Numerator','Denominator','Expression','Aggregation','Unit','Eligible population','Exclusions','Events and source','Owner / cadence','Missing evidence','Gaming and limits']) assert.equal(contract.split(`| ${field} |`).length, 2, `${metric.title}: ${field}`);
}
assert.equal(readdirSync('docs/strategy/measurement').filter(p => p.endsWith('.mdx')).length, 19);
assert(!existsSync('docs/strategy/reference/measurement-contracts.mdx'));
for (const part of manifest.shared) {
const page = read(`docs/strategy/measurement/${part.slug}.mdx`);
const body = page.split('{/* preserved:start */}\n')[1]?.split('\n{/* preserved:end */}')[0];
// Only the cross-page navigation wording changes; hash all original substance.
const original = body.replace('Use the [metric definitions](./index.mdx#metric-definitions)', 'Use the metric contracts below');
assert.equal(createHash('sha256').update(original).digest('hex'), part.sha256);
}
});
+65
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@@ -0,0 +1,65 @@
// Native Workflow v2 owns node geometry, mainPath and routing. The portal adds
// multiline typography: upstream's three single-line labels are too small for
// a Roadmap reading view. Do not change the pinned vendor or graph semantics.
const escape = text => text.replaceAll('&', '&amp;').replaceAll('<', '&lt;').replaceAll('>', '&gt;').replaceAll('"', '&quot;');
const wrap = (text, limit = 21) => {
const lines = [];
for (const word of text.split(/\s+/)) {
if (!lines.length || `${lines.at(-1)} ${word}`.length > limit) lines.push(word);
else lines[lines.length - 1] += ` ${word}`;
}
return lines;
};
export function roadmapViewer(html, spec) {
if (spec.diagram_type !== 'workflow' || spec.schema_version !== 2 || ![2, 6].includes(spec.nodes.length)) throw new Error('Roadmap workflow contract drift');
const boxes = [];
for (const [index, node] of spec.nodes.entries()) {
const start = html.indexOf(`<g id="node-${node.id}"`);
const next = html.indexOf('<text data-node-label=', start);
const end = html.indexOf('</g>', next) + 4;
if (start < 0 || next < start || end < next) throw new Error(`Roadmap node drift: ${node.id}`);
const original = html.slice(start, end);
const rect = /<rect x="([\d.-]+)" y="([\d.-]+)" width="([\d.]+)" height="([\d.]+)"/.exec(original);
if (!rect || (original.match(/<text /g) || []).length !== 2) throw new Error(`Roadmap text contract drift: ${node.id}`);
const [x,y,w,h] = rect.slice(1).map(Number);
boxes.push({x,y,w,h});
const text = (value, top, size, cls, attrs = 'data-detail="context"') => {
const lines = wrap(value, size === 30 ? 18 : 21);
const maxLines = top === 160 ? 3 : 2;
if (lines.length > maxLines || lines.some(line => line.length > 21)) throw new Error(`Roadmap copy exceeds card capacity: ${node.id}`);
return `<text x="${x+24}" y="${y+top}" font-size="${size}" class="${cls}" ${attrs}>${lines.map((line,i) => `<tspan x="${x+24}" dy="${i ? 34 : 0}">${escape(line)}</tspan>`).join('')}</text>`;
};
if (!node.sublabel || node.tag || /Output:|Exit:|\n/.test(node.sublabel)) throw new Error(`Roadmap content contract drift: ${node.id}`);
const number = spec.nodes.length === 6 ? `Step ${index+1}` : spec.nodes[0].id === 'skills' ? `Stage ${index+1}` : index === 0 ? 'First' : 'Then';
const content = text(number, 40, 26, 't-primary', 'data-stage-number="" font-weight="700"')
+ text(node.label, 88, 30, 't-primary', 'data-node-label="" font-weight="700"')
+ text(node.sublabel, 160, 26, 't-muted');
// Preserve native node title/metadata and rectangles; replace sigil/text only.
// Sigils are nested SVG groups. Anchor on the two native node rectangles.
const rectangles = [...original.matchAll(/<rect\b[^>]*\/>/g)];
if (rectangles.length !== 2) throw new Error('Roadmap shape contract drift');
const prefixEnd = rectangles[1].index + rectangles[1][0].length;
const replacement = original.slice(0,prefixEnd).replaceAll('rx="6"', 'rx="0"') + content + '</g>';
html = html.slice(0,start) + replacement + html.slice(end);
}
// The native mobile return channel sits outside the card column.
const left = Math.min(...boxes.map(b => b.x)) - (spec.edges.some(e => e.route === 'return-left') ? 80 : 12);
const top = Math.min(...boxes.map(b => b.y)) - 12;
const width = Math.max(...boxes.map(b => b.x+b.w)) - left + 12;
const height = Math.max(...boxes.map(b => b.y+b.h)) - top + 12;
// One editorial lane; its title/frame would repeat the page's framing.
html = html.replace(/<rect\b[^>]*data-composition-frame-kind="lane"[^>]*\/>\s*<text\b[^>]*>[\s\S]*?<\/text>/g, '');
const roots = [...html.matchAll(/<svg\b[^>]*role="img"[^>]*>/g)];
if (roots.length !== 1) throw new Error('Roadmap SVG contract drift');
const root = roots[0][0].replace(/viewBox="[^"]*"/, `viewBox="${left} ${top} ${width} ${height}"`);
const styles = `<style id="eldorado-roadmap-typography">
html[data-embed="true"] .diagram-container > svg {max-height:calc(100vh - 84px);}
[data-node-id] text {font-family: Arial, sans-serif;}
svg[data-preset="classic"] [data-node-id] > rect.c-backend,
svg[data-preset="editorial"] [data-node-id] > rect.c-backend {fill:var(--panel); stroke:var(--border);}
.c-grid {opacity:0;}
</style>`;
html = html.replace(roots[0][0], root + styles);
return html;
}
+35
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@@ -0,0 +1,35 @@
import {test} from 'node:test';
import assert from 'node:assert/strict';
import {readFileSync, writeFileSync, mkdtempSync, rmSync, mkdirSync} from 'node:fs';
import {execFileSync} from 'node:child_process';
import {roadmapViewer} from './roadmap-viewer.mjs';
for (const name of ['strategy-roadmap', 'strategy-roadmap-adoption', 'strategy-roadmap-loop']) for (const suffix of ['', '-mobile']) test(`${name}${suffix} retains graph and passes final composition`, () => {
mkdirSync('.cache', {recursive:true});
const dir = mkdtempSync('.cache/roadmap-test-');
try {
const source = `diagrams/${name}${suffix}.workflow.json`;
const spec = JSON.parse(readFileSync(source, 'utf8'));
const output = `${dir}/index.html`;
execFileSync(process.execPath, ['vendor/archify/renderers/workflow/render-workflow.mjs', source, output], {env:{...process.env, ARCHIFY_UPDATE_CHECK_DISABLED:'1'}});
const native = readFileSync(output, 'utf8');
const styled = roadmapViewer(native, spec);
const graph = html => [...html.matchAll(/<path\b[^>]*data-edge-id="[^"]+"[^>]*>/g)].map(m => m[0]);
assert.equal(graph(native).length, spec.edges.length);
assert.deepEqual(graph(styled), graph(native), 'native paths must not be rewritten');
for (const node of spec.nodes) assert(styled.includes(`data-node-id="${node.id}"`));
assert.equal((styled.match(/<text data-node-label=/g) || []).length, 0, 'single-line preview replaced');
assert(styled.includes('eldorado-roadmap-typography'));
writeFileSync(output, styled);
const checked = JSON.parse(execFileSync(process.execPath, ['vendor/archify/bin/archify.mjs','check',output,'--json'], {encoding:'utf8', env:{...process.env, ARCHIFY_UPDATE_CHECK_DISABLED:'1'}}));
assert(checked.ok);
assert.equal(checked.composition.status, 'pass');
assert.equal(checked.composition.metrics.properCrossings, 0);
assert.equal(checked.composition.metrics.labelCanvasOverflowIssues, 0);
assert.throws(() => roadmapViewer('', spec), /drift/);
const oversized = structuredClone(spec);
oversized.nodes[0].sublabel = 'Too much copy '.repeat(20);
assert.throws(() => roadmapViewer(native, oversized), /capacity/);
assert.throws(() => roadmapViewer(native, {...spec,diagram_type:'architecture'}), /contract drift/);
} finally {rmSync(dir, {recursive:true, force:true});}
});
+34
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@@ -0,0 +1,34 @@
import {test} from 'node:test';
import assert from 'node:assert/strict';
import {readFileSync} from 'node:fs';
const read = path => readFileSync(path, 'utf8');
export const views = {
'strategy-roadmap': ['skills', 'autonomy'],
'strategy-roadmap-adoption': ['delivery', 'remaining'],
'strategy-roadmap-loop': ['understand', 'baseline', 'topology', 'use', 'collect', 'reassess'],
};
test('Roadmap has three visual levels and preserves human direction and Delivery discovery', () => {
const page = read('docs/strategy/roadmap.mdx');
const visible = page.split('<details>')[0];
assert.deepEqual([...visible.matchAll(/<ArchifyDiagram name="([^"]+)"/g)].map(m => m[1]), Object.keys(views));
assert.deepEqual([...visible.matchAll(/^## (.+)$/gm)].map(m => m[1]), ['Two stages toward Target', 'Stage 1: Delivery first', 'Improve within each phase', 'Delivery in practice']);
for (const marker of ['Humans direct, guide and review throughout', 'standardizes skills', 'foundation for Stage 2', 'future Autonomous Agent', 'not deployed autonomy', 'order is not yet decided', 'Delivery keeps improving', 'not as six global roadmap stages', 'what skills exist, how they relate, when they are used and how they work together', 'codebase structure', 'existing principles', 'system-logic source', 'tests', 'builds and packaging', 'deployments', 'practices, tooling, controls and problems', 'metrics/KPIs and a baseline', 'friction and feedback', './measurement/index.mdx', './target-operating-model.mdx']) assert(visible.includes(marker), marker);
for (const marker of ['revocation','exact-artifact approvals','idempotency','human takeover','sensitive decisions','security findings','reproducible baseline']) assert(page.includes(marker), marker);
assert(!/## [1-5]\.|Prepare foundations|Sustain and improve/.test(page));
});
for (const [name, ids] of Object.entries(views)) test(`${name}: native graph, mobile parity and loop semantics`, () => {
const variants = ['', '-mobile'].map(suffix => JSON.parse(read(`diagrams/${name}${suffix}.workflow.json`)));
for (const [index, d] of variants.entries()) {
assert.equal(d.schema_version, 2);
assert.equal(d.diagram_type, 'workflow');
assert.deepEqual(d.mainPath, ids.length === 6 ? ids.slice(0,3) : ids);
assert.deepEqual(d.nodes.map(n => n.id), ids);
assert.deepEqual(d.edges.filter(e => e.role === 'main').map(e => [e.from,e.to]), ids.slice(1).map((id,i) => [ids[i],id]));
assert.deepEqual(d.edges.filter(e => e.role === 'return').map(e => [e.from,e.to]), ids.length === 6 ? [['reassess','understand']] : []);
if (index) assert(d.nodes.every(n => n.col === 0));
assert(d.nodes.every(n => n.sublabel && !n.tag && n.height === 240));
}
const semantics = d => ({nodes:d.nodes.map(({col,yOffset,...n}) => n), edges:d.edges.map(({fromSide,toSide,route,...e}) => e)});
assert.deepEqual(semantics(variants[0]),semantics(variants[1]));
});
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import {test} from 'node:test';
import assert from 'node:assert/strict';
import {readFileSync} from 'node:fs';
const read = p => readFileSync(p, 'utf8');
const stages = ['Scope', 'Architecture', 'UI/UX', 'Planning', 'Delivery', 'UAT', 'Security', 'Releases'];
test('Strategy opens at the canonical autonomous lifecycle', () => {
assert.match(read('sidebars/strategy.ts'), /strategySidebar:\s*\[\s*'target-operating-model',\s*'roadmap'/);
assert.match(read('docs/strategy/target-operating-model.mdx'), /^sidebar_label: Target$/m);
for (const id of ['target-operating-model']) {
const page = read(`docs/strategy/${id}.mdx`);
const primary = page.split('<details>')[0];
assert(primary.includes('name="strategy-target"'));
assert(primary.includes('autonomous agent'));
assert(primary.includes('direct, guide and review'));
assert(primary.includes('Scope → Architecture → UI/UX → Planning → Delivery → UAT → Security → Releases → Scope'));
assert(primary.includes('human-controlled AI Agent'));
assert(!/code[ -]agent/i.test(page));
assert(primary.includes('TO-BE'));
assert(!/only routes|People authorize|independent gates protect release/.test(primary));
}
});
test('both target diagrams have eight stages, eight governed phases and eight human-controlled contributors', () => {
for (const suffix of ['', '-mobile']) {
const d = JSON.parse(read(`diagrams/strategy-target${suffix}.architecture.json`));
const ids = stages.map(label => d.components.find(n => n.label === label)?.id);
assert(ids.every(Boolean));
assert.equal(new Set(ids).size, 8);
const flow = d.connections.filter(e => ids.includes(e.from) && ids.includes(e.to));
assert.deepEqual(flow.map(e => [e.from, e.to]), ids.map((id, i) => [id, ids[(i + 1) % ids.length]]));
assert.match(flow.at(-1).label, /Repeat/);
assert(d.components.some(n => n.id === 'agent' && n.label === 'Autonomous agent' && n.sublabel === 'Human Controlled'));
assert(!d.components.some(n => n.id === 'humans' || n.label === 'Humans'));
assert(!d.connections.some(e => e.id === 'human-direction' || e.from === 'humans' || e.to === 'humans'));
assert.equal(d.connections.length, 24);
assert.deepEqual(d.connections.filter(e => e.from === 'agent').map(e => e.to), ids);
const contributors = d.components.filter(n => n.id.startsWith('code-'));
assert.equal(contributors.length, 8);
assert(contributors.every(n => n.label === 'AI Agent' && n.sublabel === 'Human-controlled'));
for (const id of ids) {
assert(d.connections.some(e => e.from === `code-${id}` && e.to === id && e.variant === 'dashed'));
assert(d.connections.some(e => e.from === 'agent' && e.to === id && e.variant === 'security'));
}
assert.equal(d.components.length, 17);
if (!suffix) {
const center = n => n.pos.map((v, i) => v + n.size[i] / 2);
const agent = center(d.components.find(n => n.id === 'agent'));
const phaseCenters = ids.map(id => center(d.components.find(n => n.id === id)));
for (const axis of [0, 1]) {
const values = phaseCenters.map(c => c[axis]);
assert.equal(agent[axis], (Math.min(...values) + Math.max(...values)) / 2);
}
for (const code of contributors) {
const phase = d.components.find(n => n.id === code.id.slice(5));
const distance = n => Math.hypot(...center(n).map((v, i) => v - agent[i]));
assert(distance(code) > distance(phase), `${code.id} is exterior`);
}
}
}
});
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import assert from 'node:assert/strict';
import {readFileSync, readdirSync, mkdirSync, writeFileSync} from 'node:fs';
import {join} from 'node:path';
const normalize = path => path.replace(/\/$/, '');
const read = path => JSON.parse(readFileSync(path, 'utf8'));
// Use Docusaurus's resolved IDs/routes and sidebar trees, not filename guesses.
export function auditSidebars(instances, entrySidebars) {
const docs = new Map();
const menus = new Map();
for (const {plugin, version, documents, sidebars} of instances) {
const ids = new Set();
for (const doc of documents) {
assert(!ids.has(doc.id), `Duplicate document ID: ${plugin}:${version}:${doc.id}`);
ids.add(doc.id);
const route = normalize(doc.path);
assert(!docs.has(route), `Duplicate document route: ${route}`);
docs.set(route, {...doc, plugin, version, menu: `${plugin}:${version}:${doc.sidebar}`});
}
for (const [name, items] of Object.entries(sidebars)) menus.set(`${plugin}:${version}:${name}`, items);
}
const links = new Map();
for (const [menu, items] of menus) {
const found = new Set();
const walk = items => {
for (const item of items) {
assert(['category', 'link', 'html'].includes(item.type), `Unresolved sidebar type: ${item.type}`);
assert(!item.unlisted, `Hidden sidebar item: ${item.label}`);
if (item.href && !/^(https?:|mailto:)/.test(item.href)) {
const route = normalize(item.href);
if (item.docId) assert.equal(docs.get(route)?.id, item.docId, `Sidebar ID/route mismatch: ${item.docId}`);
assert(!found.has(route), `Duplicate sidebar route in ${menu}: ${route}`);
found.add(route);
}
if (item.type === 'category') walk(item.items);
}
};
walk(items);
links.set(menu, found);
}
const reachable = new Set(entrySidebars);
for (const menu of reachable) {
assert(menus.has(menu), `Unknown navigation sidebar: ${menu}`);
for (const route of links.get(menu)) {
const doc = docs.get(route);
if (doc) reachable.add(doc.menu);
}
}
for (const [route, doc] of docs) {
assert(reachable.has(doc.menu), `Unreachable sidebar for ${doc.plugin}:${doc.id}`);
assert(links.get(doc.menu)?.has(route), `Missing sidebar document: ${doc.plugin}:${doc.id}`);
}
return [...docs.entries()].map(([route, doc]) => ({route, id:doc.id, plugin:doc.plugin, sidebar:doc.sidebar}));
}
export async function verifySidebarCoverage() {
const global = read('.docusaurus/globalData.json')['docusaurus-plugin-content-docs'];
assert(global && Object.keys(global).length, 'No generated document inventory');
const instances = [];
for (const [plugin, data] of Object.entries(global)) {
const folder = `.docusaurus/docusaurus-plugin-content-docs/${plugin}/p`;
const resolved = readdirSync(folder).filter(f => f.endsWith('.json')).map(f => read(join(folder, f)).version);
for (const version of data.versions) {
const matches = resolved.filter(v => v.version === version.name);
assert.equal(matches.length, 1, `Missing/duplicate resolved version: ${plugin}:${version.name}`);
instances.push({plugin, version:version.name, documents:version.docs, sidebars:matches[0].docsSidebars});
}
}
const {default:config} = await import('../.docusaurus/docusaurus.config.mjs');
const entries = config.themeConfig.navbar.items.filter(i => i.type === 'docSidebar').map(i => `${i.docsPluginId || 'default'}:current:${i.sidebarId}`);
const documents = auditSidebars(instances, entries);
const routes = new Set(documents.map(d => `${d.route.replace(config.baseUrl, '')}/index.html`));
const exclusions = [];
const html = readdirSync('build', {recursive:true}).filter(f => f.endsWith('.html')).sort();
for (const file of html) {
if (routes.delete(file)) continue;
let reason;
if (file === 'index.html') reason = 'Dedicated React homepage, not a documentation page';
else if (file === '404.html') reason = 'Docusaurus not-found system page';
else if (file === 'search/index.html') reason = 'Local-search results UI, not a documentation page';
else if (file === 'strategy/index.html') {
assert(readFileSync(join('build',file),'utf8').includes('http-equiv="refresh"'), 'Strategy alias must remain a redirect');
reason = 'Legacy Strategy redirect alias to Target';
} else if (file === 'strategy/reference/measurement-contracts/index.html') {
const body = readFileSync(join('build',file),'utf8');
assert(body.includes('window.location.replace') && body.includes('name="robots" content="noindex"') && !body.includes('<article'), 'Metric alias must remain a non-indexed redirect');
assert.equal(body, readFileSync(join('static',file),'utf8'));
reason = 'Legacy measurement-contracts hash-aware redirect to canonical Measurement pages';
} else if (file.startsWith('diagrams/') && readFileSync(join('build',file),'utf8').includes('<svg')) {
assert.equal(readFileSync(join('build',file),'utf8'), readFileSync(join('static',file),'utf8'), `Viewer must match generated static asset: ${file}`);
reason = 'Standalone diagram viewer asset, not documentation';
}
assert(reason, `Unclassified published HTML route: ${file}`);
exclusions.push({file, reason});
}
assert.equal(routes.size, 0, `Missing published docs: ${[...routes]}`);
// Check all local links and anchors on every document, not only selected Strategy pages.
for (const {route} of documents) {
const file = `build/${route.replace(config.baseUrl, '')}/index.html`;
const body = readFileSync(file, 'utf8');
for (const [, href] of body.matchAll(/href="([^" ]+)"/g)) {
if (!href.startsWith(config.baseUrl) && !href.startsWith('#')) continue;
const url = new URL(href, `https://docs.invalid${route}/`);
let target = url.pathname.slice(config.baseUrl.length);
if (!target || target.endsWith('/')) target += 'index.html';
else if (!target.split('/').at(-1).includes('.')) target += '/index.html';
const targetBody = readFileSync(join('build', decodeURIComponent(target)), 'utf8');
if (url.hash) assert(targetBody.includes(`id="${decodeURIComponent(url.hash.slice(1))}"`), `Broken anchor: ${route} -> ${href}`);
}
}
mkdirSync('.cache', {recursive:true});
writeFileSync('.cache/sidebar-coverage.json', JSON.stringify({documents, exclusions}, null, 2));
console.log(`PASS: ${documents.length} published docs reachable in resolved sidebars; ${exclusions.length} classified non-doc HTML routes; all doc links/anchors checked`);
return {documents, exclusions};
}
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import {test} from 'node:test';
import assert from 'node:assert/strict';
import {auditSidebars} from './sidebar-coverage.mjs';
const fixture = () => [{plugin:'strategy', version:'current', documents:[
{id:'overview', path:'/strategy/overview/', sidebar:'main'},
{id:'nested/reference', path:'/strategy/reference/', sidebar:'main'},
], sidebars:{main:[{type:'category', label:'Stage', href:'/strategy/overview', items:[
{type:'category', label:'Reference', items:[{type:'link', docId:'nested/reference', href:'/strategy/reference'}]},
]}]}}];
const entries = ['strategy:current:main'];
test('resolved nested entries and linked category overviews both count', () => {
assert.equal(auditSidebars(fixture(), entries).length, 2);
});
test('missing docs fail even if Docusaurus assigns a displayed sidebar', () => {
const data = fixture();
data[0].sidebars.main[0].items = [];
assert.throws(() => auditSidebars(data, entries), /Missing sidebar document/);
});
test('new publishable docs and absent category overview links fail closed', () => {
const data = fixture();
data[0].documents.push({id:'new', path:'/new'});
assert.throws(() => auditSidebars(data, entries), /Unreachable sidebar/);
const withoutLink = fixture();
delete withoutLink[0].sidebars.main[0].href;
assert.throws(() => auditSidebars(withoutLink, entries), /Missing sidebar document/);
});
test('duplicate normalized routes and duplicate sidebar entries fail', () => {
const data = fixture();
data[0].documents.push({...data[0].documents[0], path:'/strategy/overview'});
assert.throws(() => auditSidebars(data, entries), /Duplicate document ID/);
data[0].documents.at(-1).id = 'different';
assert.throws(() => auditSidebars(data, entries), /Duplicate document route/);
const duplicate = fixture();
duplicate[0].sidebars.main.push({type:'link', href:'/strategy/overview/'});
assert.throws(() => auditSidebars(duplicate, entries), /Duplicate sidebar route/);
});
test('unlisted entries and unresolved sidebar types fail', () => {
const data = fixture();
data[0].sidebars.main[0].unlisted = true;
assert.throws(() => auditSidebars(data, entries), /Hidden sidebar item/);
data[0].sidebars.main[0] = {type:'autogenerated'};
assert.throws(() => auditSidebars(data, entries), /Unresolved sidebar type/);
});
test('disconnected plugin menus fail, cross-plugin sidebar links make them reachable', () => {
const data = fixture();
data.push({plugin:'default', version:'current', documents:[{id:'help', path:'/docs/help', sidebar:'docs'}], sidebars:{docs:[{type:'link', href:'/docs/help'}]}});
assert.throws(() => auditSidebars(data, entries), /Unreachable sidebar/);
data[0].sidebars.main.push({type:'link', href:'/docs/help/'});
assert.equal(auditSidebars(data, entries).length, 3);
});
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import test from 'node:test';
import assert from 'node:assert/strict';
import {readFileSync} from 'node:fs';
import {calculate} from './ai-kpi.mjs';
const read = path => readFileSync(path, 'utf8');
test('Skills Measurement is a visible optional registry, separate from workflow application', () => {
const page = read('docs/strategy/measurement/index.mdx');
assert.match(page, /title: Skills Measurement\nsidebar_label: Measurement/);
for (const heading of ['Establish the baseline', 'Measure the pilot', 'Extend collection as adoption grows', 'Keep the collection running']) assert(!page.includes(heading), heading);
assert(page.includes('Registry inclusion does not require a metric to be used, collected or baselined'));
assert(page.includes('../baseline.mdx'));
assert(!page.includes('<details>'));
assert(page.includes('./collection-and-safeguards.mdx'));
assert(!page.includes('Is AI-assisted work worth continuing?'));
for (const word of ['candidate', 'not installed', 'applicability', 'calculation', 'inputs', 'limitations', 'implementation status']) assert(page.includes(word), word);
});
test('all sixteen metric definitions remain in the reference with explicit implementation limits', () => {
const manifest = JSON.parse(read('research/ai-adoption/measurement-migration.json'));
const page = read('docs/strategy/measurement/index.mdx') + read('docs/strategy/measurement/collection-and-safeguards.mdx');
const model = JSON.parse(read('research/ai-adoption/strategy-model.json'));
for (const k of model.kpis) {
const section = read(`docs/strategy/${manifest.metrics.find(m => m.title === k.name).docId}.mdx`);
assert(section, k.name);
for (const field of ['Numerator','Denominator','Expression','Aggregation','Unit','Eligible population','Exclusions','Events and source','Owner / cadence','Missing evidence','Gaming and limits']) assert(section.includes(`| ${field} |`));
}
for (const text of ['9 prototype calculations', '7 unimplemented metrics', 'no network collectors', '30 days', '12 months', 'below five people', 'Missing telemetry is unknown']) assert(page.includes(text), text);
});
test('two groups exhaustively classify the sixteen canonical contracts without duplication', () => {
const page = read('docs/strategy/measurement/index.mdx');
const manifest = JSON.parse(read('research/ai-adoption/measurement-migration.json'));
assert.deepEqual([...page.matchAll(/^### (.+)$/gm)].map(m => m[1]), ['Workflow effectiveness', 'Skills effectiveness & health']);
const rows = [...page.matchAll(/^\d+\. \[([^\]]+)\]\(\.\/([^/]+)\.mdx\) — \*\*(Prototype calculation|Unimplemented metric)\.\*\*/gm)];
assert.equal(rows.length, 16);
assert.equal(new Set(rows.map(m => m[2])).size, 16);
assert.deepEqual(rows.map(m => m[1]).sort(), manifest.metrics.map(m => m.title).sort());
assert.equal(rows.filter(m => m[3] === 'Prototype calculation').length, 9);
assert.equal(rows.filter(m => m[3] === 'Unimplemented metric').length, 7);
const [workflow, skills] = page.split('### Workflow effectiveness')[1].split('### Skills effectiveness & health');
assert.equal([...workflow.matchAll(/^\d+\. /gm)].length, 11);
assert.equal([...skills.matchAll(/^\d+\. /gm)].length, 5);
for (const slug of ['validated-task-success', 'confirmed-policy-effects', 'cost-per-accepted-outcome', 'workflow-specific-business-acceptance']) assert(workflow.includes(`./${slug}.mdx`));
for (const slug of ['skill-selection-precision', 'skill-selection-recall', 'supported-bundle-coverage', 'approved-workflow-adoption', 'skills-within-substantive-review-window']) assert(skills.includes(`./${slug}.mdx`));
for (const marker of ['N/A, not zero', 'More adoption does not prove improved work', 'Before/after trends alone are not causal evidence', 'Sandbox/evaluation cases remain excluded']) assert(page.includes(marker), marker);
});
test('workflow task-success contract retains evaluation exclusions and explains conditional skill slices', () => {
const page = read('docs/strategy/measurement/validated-task-success.mdx');
assert.equal((page.match(/\| Expression \|/g) || []).length, 1);
for (const marker of ['sandbox/evaluation tasks', 'Overlapping skill slices must not be summed', 'remains excluded by this contract', 'does not introduce an implemented skill-evaluation metric', 'N/A, not a zero workflow success rate']) assert(page.includes(marker), marker);
for (const name of ['baseline', 'skills-adoption', 'skills-maintenance', 'stage-01-skills-adoption']) {
const text = read(`docs/strategy/${name}.mdx`);
if (name !== 'stage-01-skills-adoption') for (const group of ['Workflow effectiveness', 'Skills effectiveness & health']) assert(text.includes(group), name);
}
});
test('published pilot arithmetic matches the executable fixture, including partial cost', () => {
const page = read('docs/strategy/skills-adoption.mdx');
const fixture = JSON.parse(read('scripts/fixtures/ai-kpi-synthetic.json'));
const report = calculate(fixture);
const success = report.kpis['validated-task-success'];
assert(page.includes(`${success.numerator} / ${success.denominator} × 100 = ${success.value_or_null}%`));
assert(page.includes(`${success.known_outcome_coverage}%`));
const cost = report.kpis['cost-per-accepted-outcome'];
assert.equal(cost.partial_estimate, true);
assert(page.includes(`EUR ${cost.numerator} / ${cost.denominator} = EUR ${cost.value_or_null}`));
assert(page.includes('partial estimate'));
const experience = report.kpis['human-experience'];
assert(page.includes(`${experience.numerator} / ${experience.denominator} = ${experience.value_or_null}`));
assert(page.includes(`${experience.denominator} / ${fixture.survey.invited} × 100 = ${experience.coverage.response_percent}%`));
});
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import {test} from 'node:test';
import assert from 'node:assert/strict';
import {readFileSync, mkdtempSync, rmSync} from 'node:fs';
import {tmpdir} from 'node:os';
import {join} from 'node:path';
import {execFileSync} from 'node:child_process';
import {skillsViewer,isSkillsStory} from './skills-viewer.mjs';
const read = p => readFileSync(p,'utf8');
const topics = ['measurement','baseline','governance','quality','adoption','maintenance'];
test('all seven Skills Adoption pages account for six diagrams and twelve sources',()=>{
let count=0;
for(const route of ['stage-01-skills-adoption',...topics.map(t=>['measurement','baseline'].includes(t)?t:`skills-${t}`)]){
const diagrams=[...read(`docs/strategy/${route === 'measurement' ? 'measurement/index' : route}.mdx`).matchAll(/<ArchifyDiagram name="([^"]+)"/g)];
assert.equal(diagrams.length,route.startsWith('stage-')?0:1);
for(const [,name] of diagrams){assert(isSkillsStory(name));for(const suffix of ['','-mobile'])JSON.parse(read(`diagrams/${name}${suffix}.architecture.json`));count++;}
}
assert.equal(count,6);assert(!isSkillsStory('strategy-target'));assert(!isSkillsStory('strategy-roadmap'));
});
for(const topic of topics) test(`${topic}: rich native source, wide desktop, mobile parity and checked adapter`,()=>{
const name=`strategy-${topic}`;const desktop=JSON.parse(read(`diagrams/${name}.architecture.json`));
const mobile=JSON.parse(read(`diagrams/${name}-mobile.architecture.json`));
const semantic = d=>d.components.map(({pos,size,...n})=>n);
assert.deepEqual(semantic(desktop),semantic(mobile));
assert(new Set(desktop.components.map(n=>n.pos[0])).size>1);
assert.equal(new Set(mobile.components.map(n=>n.pos[0])).size,1);
for(const n of desktop.components){assert(n.tag);assert(n.sublabel);assert(n.sublabel.split('\n').length<=4);}
const dir=mkdtempSync(join(tmpdir(),'skills-viewer-'));
try{
const path=join(dir,'native.html');
execFileSync(process.execPath,['vendor/archify/renderers/architecture/render-architecture.mjs',`diagrams/${name}.architecture.json`,path]);
const native=read(path);const html=skillsViewer(native,desktop);
assert.equal((html.match(/<g\b[^>]*data-node-id=/g)||[]).length,desktop.components.length);
assert.equal((html.match(/<text data-node-label=/g)||[]).length,0); // Adapter uses explicit position before semantic attributes.
assert.equal((html.match(/data-node-label=""/g)||[]).length,desktop.components.length);
assert(html.includes('eldorado-skills-typography'));
assert.throws(()=>skillsViewer(native.replace('data-node-id="'+desktop.components[0].id+'"','data-node-id="missing"'),desktop));
const bad=structuredClone(desktop);bad.components[0].sublabel='';assert.throws(()=>skillsViewer(native,bad));
}finally{rmSync(dir,{recursive:true,force:true});}
});
test('domain contracts retain human authority, honest measures and Delivery-first rollout',()=>{
const text=t=>JSON.stringify(JSON.parse(read(`diagrams/strategy-${t}.architecture.json`)));
assert(text('governance').includes('Author is not sole approver'));
assert(text('quality').includes('Critical effect blocks'));
assert(text('adoption').includes('Delivery first')&&text('adoption').includes('Later order undecided'));
assert(text('adoption').includes('No quotas or rankings'));
for(const marker of ['Workflow effectiveness','Skills effectiveness & health','16 optional candidate contracts','No mandatory collection','Before / after is not causality','9 prototype / 7 unimplemented'])assert(text('measurement').includes(marker),marker);
assert(text('maintenance').includes('No automatic reinstatement'));
});
test('topic compositions explain distinct relationships rather than a fixed card count',()=>{
const spec=t=>JSON.parse(read(`diagrams/strategy-${t}.architecture.json`));
const has=(d,a,b)=>assert(d.connections.some(e=>e.from===a&&e.to===b),`${a} → ${b}`);
const g=spec('governance');const steps=g.components.filter(n=>/^0[1-6]/.test(n.label));
assert.equal(steps.length,6);
for(let i=1;i<steps.length;i++){assert(steps[i].pos[0]>steps[i-1].pos[0]);assert(steps[i].pos[1]>steps[i-1].pos[1]);has(g,steps[i-1].id,steps[i].id);}
has(g,'approve','owner');has(g,'distribute','withdraw');
const q=spec('quality');for(const id of ['selection','safety','artifact','outcome'])has(q,id,'gate');has(q,'gate','accept');has(q,'gate','rework');
const a=spec('adoption');for(const [x,y] of [['human','agent'],['agent','human'],['agent','learn'],['learn','delivery'],['learn','expand'],['human','expand']])has(a,x,y);
const m=spec('measurement');for(const [x,y] of [['workflow','compare'],['compare','interpret'],['skills','observe'],['observe','improve'],['interpret','improve']])has(m,x,y);
const b=spec('baseline');for(const [x,y] of [['workflow','selection'],['selection','evidence'],['evidence','position'],['position','comparison']])has(b,x,y);
const c=spec('maintenance');for(const [x,y] of [['observe','triage'],['triage','change'],['change','validate'],['validate','release'],['release','observe'],['triage','safe'],['safe','observe'],['triage','retire'],['triage','contain'],['contain','change']])has(c,x,y);
});
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// Native editable geometry and edges; scoped editorial typography for Stage 01.
export const isSkillsStory = name => /^strategy-(governance|quality|adoption|measurement|baseline|maintenance)(-mobile)?$/.test(name);
const escape = text => text.replaceAll('&', '&amp;').replaceAll('<', '&lt;').replaceAll('>', '&gt;').replaceAll('"', '&quot;');
export function skillsViewer(html, spec) {
if (spec.diagram_type !== 'architecture' || !spec.components.length) throw new Error('Skills story contract drift');
const detailSize = spec.meta.output.includes('-mobile/') ? 34 : 32;
for (const node of spec.components) {
const pattern = new RegExp(`<g\\b[^>]*data-node-id="${node.id}"[^>]*>[\\s\\S]*?<text data-node-label=[\\s\\S]*?</g>`);
const match = html.match(pattern);
if (!match) throw new Error(`Missing Skills node: ${node.id}`);
const original = match[0];
const rectangles = [...original.matchAll(/<rect\b[^>]*class="c-[^"]+"[^>]*\/>/g)];
if (rectangles.length !== 2) throw new Error('Skills shape contract drift');
const [x,y] = node.pos;
const lines = node.sublabel.split('\n');
if (!node.tag || !node.sublabel || lines.length > 4) throw new Error(`Skills copy exceeds capacity: ${node.id}`);
const text = (value, top, size, attrs) => `<text x="${x+28}" y="${y+top}" font-size="${size}" ${attrs}>${escape(value)}</text>`;
const content = text(node.tag, 40, detailSize, 'class="t-muted" data-detail="context"')
+ text(node.label, 89, 36, 'class="t-primary" data-node-label="" font-weight="700"')
+ lines.map((line,i) => text(line, 138+i*42, detailSize, 'class="t-primary" data-detail="context"')).join('');
const prefix = original.slice(0,rectangles[1].index+rectangles[1][0].length).replaceAll('rx="6"','rx="0"');
html = html.replace(original,prefix+content+'</g>');
}
const roots = [...html.matchAll(/<svg\b[^>]*role="img"[^>]*>/g)];
if (roots.length !== 1) throw new Error('Skills SVG contract drift');
const [width,height] = spec.meta.viewBox;
const root = roots[0][0].replace(/viewBox="[^"]*"/,`viewBox="0 0 ${width} ${height}"`);
// Embedded in SVG so downloaded files retain typography without the viewer.
html = html.replace(roots[0][0],root+`<style id="eldorado-skills-typography">
[data-node-id] text {font-family:Arial,sans-serif;}
rect[fill="url(#grid)"] {opacity:0;}
[data-node-id] > rect:not(.c-mask) {stroke-width:3;}
[data-edge-id] {opacity:1;}
</style>`);
// Native labels use tiny technical annotations. Enlarge both text and mask,
// retaining the native edge identity, routing and explicit label position.
html = html.replace(/(<g data-detail="context"[^>]*data-edge-id[^>]*>)([\s\S]*?)(<\/g>)/g, (all,open,body,close) => {
const text = body.match(/<text x="([^"]+)" y="([^"]+)"([^>]*)>([\s\S]*?)<\/text>/);
if (!text) throw new Error('Skills edge label contract drift');
const x=Number(text[1]), y=Number(text[2]), width=text[4].replace(/&[^;]+;/g,'x').length*17+24;
return open+`<rect x="${x-width/2}" y="${y-34}" width="${width}" height="44" class="c-mask"/>`+text[0].replace('font-size="8"',`font-size="${detailSize}"`)+close;
});
return html;
}
+53
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@@ -0,0 +1,53 @@
import {test} from 'node:test';
import assert from 'node:assert/strict';
import {readFileSync, existsSync} from 'node:fs';
import {runInNewContext} from 'node:vm';
import ts from 'typescript';
const read = p => readFileSync(p, 'utf8');
test('Strategy has Target, Roadmap, a linked Skills Adoption category and Autonomous Agent', () => {
const compiled = ts.transpileModule(read('sidebars/strategy.ts'), {compilerOptions:{module:ts.ModuleKind.CommonJS}}).outputText;
const sandbox = {exports:{}};
runInNewContext(compiled, sandbox);
const sidebar = JSON.parse(JSON.stringify(sandbox.exports.default.strategySidebar));
assert.deepEqual(sidebar, ['target-operating-model', 'roadmap', {
type:'category', label:'Stage - 01 - Skills Adoption',
link:{type:'doc', id:'stage-01-skills-adoption'}, collapsed:true,
items:[
{type:'category', label:'Measurement', collapsed:true, link:{type:'doc', id:'measurement/index'}, items:[
...JSON.parse(read('research/ai-adoption/measurement-migration.json')).metrics.map(m => m.docId),
'measurement/collection-and-safeguards','measurement/synthetic-example',
]},
{type:'doc', id:'baseline', label:'Baseline'},
{type:'doc', id:'skills-governance', label:'Governance'},
{type:'doc', id:'skills-quality', label:'Quality'},
{type:'doc', id:'skills-adoption', label:'Adoption'},
{type:'doc', id:'skills-maintenance', label:'Maintenance'},
],
}, 'stage-02-autonomous-agent']);
assert.match(read('docs/strategy/target-operating-model.mdx'), /^sidebar_label: Target$/m);
assert.match(read('docusaurus.config.ts'), /type: 'docSidebar', docsPluginId: 'strategy', sidebarId: 'strategySidebar', label: 'Strategy'/);
});
test('stage overviews explain the foundation and future without replacing topic content', () => {
const first = read('docs/strategy/stage-01-skills-adoption.mdx');
const second = read('docs/strategy/stage-02-autonomous-agent.mdx');
for (const [id, title, page] of [
['stage-01-skills-adoption', 'Stage - 01 - Skills Adoption', first],
['stage-02-autonomous-agent', 'Stage - 02 - Autonomous Agent', second],
]) {
assert(page.includes(`id: ${id}\ntitle: ${title}`));
for (const link of ['./roadmap.mdx', './target-operating-model.mdx']) assert(page.includes(link));
}
for (const id of ['measurement/index','baseline','skills-governance','skills-quality','skills-adoption','skills-maintenance']) assert(first.includes(`./${id}.mdx`));
for (const marker of ['human + AI Agent','Delivery first','order is not yet decided','KPIs','baseline','topology','feedback','new current situation']) assert(first.includes(marker), marker);
for (const marker of ['future','proven skills','measurements','working practices','direction and review','not deployed autonomy','approved KPI thresholds']) assert(second.includes(marker), marker);
assert.match(read('docs/strategy/measurement/index.mdx'), /^title: Skills Measurement\nsidebar_label: Measurement$/m);
});
test('old Strategy entry redirects to Target instead of maintaining a second document', () => {
assert(!existsSync('docs/strategy/index.mdx'));
assert.match(read('docusaurus.config.ts'), /'@docusaurus\/plugin-client-redirects'/);
assert.match(read('docusaurus.config.ts'), /from: '\/strategy\/', to: '\/strategy\/target-operating-model\/'/);
});
+22 -14
View File
@@ -6,42 +6,50 @@ const model = JSON.parse(read('research/ai-adoption/strategy-model.json'));
test('every strategy page leads with a compact diagram story and closes its references', () => {
for (const {id} of model.pages) {
const page = read(`docs/strategy/${id}.mdx`);
const page = read(`docs/strategy/${id === 'measurement' ? 'measurement/index' : id}.mdx`);
const narrative = page.split('<div className="strategy-content">')[1].replace(/<details>[\s\S]*?<\/details>/g, '');
assert.equal((narrative.match(/<ArchifyDiagram /g) || []).length, 1, id);
assert.equal((narrative.match(/<ArchifyDiagram /g) || []).length, id === 'roadmap' ? 3 : 1, id);
assert(narrative.includes(' story />'), id);
assert(page.indexOf(' story />') < page.indexOf('<details>'), id);
assert(!page.includes('<details>') || page.indexOf(' story />') < page.indexOf('<details>'), id);
assert(!/<details\s+open/.test(page), id);
assert.equal((page.match(/<details>/g) || []).length, (page.match(/<\/details>/g) || []).length, id);
assert.equal((narrative.match(/^## /gm) || []).length, 1, id);
assert.equal((narrative.match(/^## /gm) || []).length, id === 'measurement' ? 2 : id === 'roadmap' ? 4 : 1, id);
assert((narrative.match(/^- /gm) || []).length <= 3, id);
assert(narrative.includes('**Next:**'), id);
assert(!narrative.includes('| ---'), id);
const words = narrative.replace(/<[^>]*>/g, '').trim().split(/\s+/).length;
assert(words <= 200, `${id}: ${words} default narrative words`);
assert(words <= (id === 'measurement' ? 1500 : id === 'roadmap' ? 600 : 200), `${id}: ${words} default narrative words`);
}
});
test('mobile story diagrams preserve the same nodes and directed relationships', () => {
for (const {id} of model.pages) {
const page = read(`docs/strategy/${id}.mdx`);
const page = read(`docs/strategy/${id === 'measurement' ? 'measurement/index' : id}.mdx`);
const name = /<ArchifyDiagram name="([^"]+)"[^>]+ story/.exec(page)[1];
if (name === 'strategy-roadmap') {
const desktop = JSON.parse(read(`diagrams/${name}.workflow.json`));
const mobile = JSON.parse(read(`diagrams/${name}-mobile.workflow.json`));
const semantic = d => ({nodes:d.nodes.map(({col,yOffset,...n}) => n), edges:d.edges.map(({fromSide,toSide,...e}) => e)});
assert.deepEqual(semantic(desktop), semantic(mobile));
continue;
}
const desktop = JSON.parse(read(`diagrams/${name}.architecture.json`));
const mobile = JSON.parse(read(`diagrams/${name}-mobile.architecture.json`));
assert(desktop.components.length >= 5 && desktop.components.length <= 7, name);
const semantic = d => ({nodes:d.components.map(({pos,size,...n})=>n),edges:d.connections.map(({fromSide,toSide,...e})=>e)});
assert(desktop.components.length >= 5, name);
const semantic = d => ({nodes:d.components.map(({pos,size,...n})=>n),edges:d.connections.map(({fromSide,toSide,route,via,labelAt,...e})=>e)});
assert.deepEqual(semantic(desktop), semantic(mobile), name);
assert(desktop.connections.every(e => e.label && e.from !== e.to), name);
assert(desktop.connections.every(e => (e.label || e.id.startsWith('govern-') || /^strategy-(governance|quality|adoption|measurement|maintenance)$/.test(name)) && e.from !== e.to), name);
assert.equal(desktop.meta.legend.mode, 'hidden');
}
});
test('all sixteen exact KPI formulas remain reachable in the closed reference', () => {
const page = read('docs/strategy/measurement.mdx');
const contracts = page.split('<summary>All 16 KPI contracts')[1].split('</details>')[0];
assert.equal((contracts.match(/^### /gm) || []).length, 16);
test('all sixteen exact KPI formulas remain reachable in the linked reference', () => {
const manifest = JSON.parse(read('research/ai-adoption/measurement-migration.json'));
assert.equal(manifest.metrics.length, 16);
for (const metric of model.kpis) {
const section = contracts.split(`### ${metric.name}\n`)[1]?.split('\n### ')[0];
const entry = manifest.metrics.find(m => m.title === metric.name);
assert(read('docs/strategy/measurement/index.mdx').includes(`./${entry.oldAnchor}.mdx`));
const section = read(`docs/strategy/${entry.docId}.mdx`);
assert(section, metric.name);
for (const label of ['Numerator','Denominator','Expression','Aggregation','Unit','Eligible population','Exclusions','Events and source','Owner / cadence','Missing evidence','Gaming and limits']) assert(section.includes(`| ${label} |`), `${metric.name}: ${label}`);
}
+10 -9
View File
@@ -3,15 +3,16 @@ import assert from 'node:assert/strict';
import {readFileSync, readdirSync} from 'node:fs';
const read = p => readFileSync(p, 'utf8');
const model = JSON.parse(read('research/ai-adoption/strategy-model.json'));
test('eight fixed strategy pages preserve target boundary and separate evidence', () => {
assert.equal(model.pages.length, 8);
assert.equal(readdirSync('docs/strategy').length, 8);
test('seven existing strategy pages and two stage overviews preserve canonical routes', () => {
assert.equal(model.pages.length, 7);
assert.deepEqual(readdirSync('docs/strategy').filter(p => p.endsWith('.mdx')).sort(),
[...model.pages.filter(p => p.id !== 'measurement').map(({id}) => `${id}.mdx`), 'stage-01-skills-adoption.mdx', 'stage-02-autonomous-agent.mdx', 'baseline.mdx'].sort());
for (const {id} of model.pages) {
const page = read(`docs/strategy/${id}.mdx`);
assert(page.includes(`id: ${id}`));
const page = read(`docs/strategy/${id === 'measurement' ? 'measurement/index' : id}.mdx`);
assert(page.includes(`id: ${id === 'measurement' ? 'index' : id}`));
assert(page.includes('Target operating model'));
assert(!/## Sources|\[\d+\]|Internal evidence mapping/.test(page));
assert(read('sidebars/strategy.ts').includes(`'${id}'`));
assert(read('sidebars/strategy.ts').includes(`'${id === 'measurement' ? 'measurement/index' : id}'`));
}
for (const teams of Object.values(model.organization)) for (const name of teams) {
assert(read('docs/organization/structure.mdx').includes(name));
@@ -19,15 +20,15 @@ test('eight fixed strategy pages preserve target boundary and separate evidence'
}
});
test('every metric has an actionable reader-facing contract', () => {
const page = read('docs/strategy/measurement.mdx');
const manifest = JSON.parse(read('research/ai-adoption/measurement-migration.json'));
assert.equal(model.kpis.length,16);
for (const k of model.kpis) {
const section=page.split(`### ${k.name}\n`)[1]?.split('\n### ')[0];
const section=read(`docs/strategy/${manifest.metrics.find(m => m.title === k.name).docId}.mdx`);
assert(section,k.name);
for (const field of ['Eligible population','Exclusions','Events and source','Owner / cadence','Missing evidence','Gaming and limits']) assert(section.includes(`| ${field} |`));
assert(section.includes(k.owner));
}
assert(page.includes('synthetic') && page.includes('not a production ingestion system'));
assert(read('docs/strategy/measurement/synthetic-example.mdx').includes('not a production ingestion system'));
});
test('diagram preserves independent release approval and no agent production authority', () => {
const d=JSON.parse(read('diagrams/ai-adoption-target.architecture.json'));
+31
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@@ -0,0 +1,31 @@
import {test} from 'node:test';
import assert from 'node:assert/strict';
import {readFileSync} from 'node:fs';
import {createRouter} from '../vendor/archify/renderers/architecture/routing.mjs';
import {segmentIntersectsRect} from '../vendor/archify/renderers/shared/geometry.mjs';
for (const suffix of ['', '-mobile']) {
test(`Target${suffix} uses shared native midpoint ports without node crossings`, () => {
const diagram = JSON.parse(readFileSync(`diagrams/strategy-target${suffix}.architecture.json`, 'utf8'));
const boxes = new Map(diagram.components.map(({id, pos: [x, y], size: [width, height]}) =>
[id, {id, x, y, width, height, cx: x + width / 2, cy: y + height / 2}]));
const router = createRouter(boxes, diagram.connections, {distinctAutomaticPorts: true});
const agent = boxes.get('agent');
for (const edge of diagram.connections.filter(edge => edge.from === 'agent')) {
const side = suffix ? 'left' : ['scope', 'architecture', 'releases'].includes(edge.to) ? 'top'
: ['planning', 'delivery', 'uat'].includes(edge.to) ? 'bottom' : edge.to === 'security' ? 'left' : 'right';
assert.equal(edge.fromSide, side, edge.id);
assert(edge.via || (edge.route && edge.route !== 'auto'), `${edge.id} must opt out of automatic port spreading`);
const expected = {top: [agent.cx, agent.y], bottom: [agent.cx, agent.y + agent.height],
left: [agent.x, agent.cy], right: [agent.x + agent.width, agent.cy]}[side];
const points = router.pathFor(edge).points;
assert.deepEqual(points[0], expected, edge.id);
for (let i = 1; i < points.length; i++) {
for (const box of boxes.values()) {
if ([edge.from, edge.to].includes(box.id)) continue;
assert(!segmentIntersectsRect({start: points[i - 1], end: points[i]}, box), `${edge.id} crosses ${box.id}`);
}
}
}
});
}
+32
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@@ -0,0 +1,32 @@
// Owned desktop-only integration, applied AFTER native artifact verification.
// Native architecture JSON has no per-edge attachment offset. Keep the central
// governance ports native; shift only these lifecycle channels on the same sides.
export const targetLifecycleOffsets = [
{id:'stage-2', from:'architecture', to:'ui-ux', x:870, shiftedX:850, y1:262.5, y2:457.5},
{id:'stage-3', from:'ui-ux', to:'planning', x:870, shiftedX:850, y1:532.5, y2:727.5},
{id:'stage-6', from:'uat', to:'security', x:330, shiftedX:350, y1:727.5, y2:532.5},
{id:'stage-7', from:'security', to:'releases', x:330, shiftedX:350, y1:457.5, y2:262.5},
];
export function targetRouting(viewer) {
for (const {id, from, to, x, shiftedX, y1, y2} of targetLifecycleOffsets) {
const oldPath = `M ${x} ${y1} L ${x} ${y2}`;
const newPath = `M ${shiftedX} ${y1} L ${shiftedX} ${y2}`;
const oldPoints = `${x},${y1};${x},${y2}`;
const newPoints = `${shiftedX},${y1};${shiftedX},${y2}`;
// Match the whole native crossover group: its mask must move with the edge.
// Trace/export use this actual path; composition checks use its point list.
const groups = [...viewer.matchAll(/<g data-graph-role="automatic-crossover"[^>]*>\s*<path\b[^>]*\/>\s*<path\b[^>]*\/>\s*<\/g>/g)]
.filter(([group]) => group.includes(`data-edge-id="${id}"`));
if (groups.length !== 1) throw new Error(`Target routing drift: ${id} group`);
const group = groups[0][0];
for (const attribute of [`data-edge-from="${from}"`, `data-edge-to="${to}"`, `data-composition-points="${oldPoints}"`, 'data-graph-role="automatic-crossover-underlay"']) {
if (!group.includes(attribute)) throw new Error(`Target routing drift: ${id} ${attribute}`);
}
if (group.split(`d="${oldPath}"`).length !== 3) throw new Error(`Target routing drift: ${id} paths`);
const shifted = group.replaceAll(`d="${oldPath}"`, `d="${newPath}"`)
.replace(`data-composition-points="${oldPoints}"`, `data-composition-points="${newPoints}"`);
viewer = viewer.replace(group, shifted);
}
return viewer;
}
+32
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@@ -0,0 +1,32 @@
import {test} from 'node:test';
import assert from 'node:assert/strict';
import {targetRouting, targetLifecycleOffsets} from './target-routing.mjs';
const fixture = targetLifecycleOffsets.map(({id, from, to, x, y1, y2}) => `<g data-graph-role="automatic-crossover" style="--step:9">
<path data-graph-role="automatic-crossover-underlay" d="M ${x} ${y1} L ${x} ${y2}"/>
<path data-edge-from="${from}" data-edge-to="${to}" data-edge-id="${id}" data-composition-points="${x},${y1};${x},${y2}" d="M ${x} ${y1} L ${x} ${y2}" marker-end="url(#arrowhead-emphasis)"/>
</g>`).join('\n');
test('Target adapter shifts precisely four paths, masks and composition points', () => {
const unrelated = '<path data-edge-id="govern-architecture" d="M 600 450 L 870 262.5"/><g data-node-id="agent"/>';
const output = targetRouting(fixture + unrelated);
assert(output.endsWith(unrelated));
let restored = output;
for (const {x, shiftedX, y1, y2} of targetLifecycleOffsets) {
assert.equal(output.split(`d="M ${shiftedX} ${y1} L ${shiftedX} ${y2}"`).length, 3);
assert(output.includes(`data-composition-points="${shiftedX},${y1};${shiftedX},${y2}"`));
restored = restored.replaceAll(`d="M ${shiftedX} ${y1} L ${shiftedX} ${y2}"`, `d="M ${x} ${y1} L ${x} ${y2}"`)
.replace(`data-composition-points="${shiftedX},${y1};${shiftedX},${y2}"`, `data-composition-points="${x},${y1};${x},${y2}"`);
}
assert.equal(restored, fixture + unrelated, 'all other bytes preserved');
});
test('Target adapter fails closed on missing, duplicate, moved or changed native edges', () => {
for (const changed of [fixture.replace('stage-2', 'missing'), fixture + fixture,
fixture.replace('870 262.5', '871 262.5'), fixture.replace('870,262.5', '871,262.5'),
fixture.replace('data-edge-from="architecture"', 'data-edge-from="scope"'),
fixture.replace('automatic-crossover-underlay', 'unknown')]) {
assert.throws(() => targetRouting(changed), /Target routing drift/);
}
assert.throws(() => targetRouting(targetRouting(fixture)), /Target routing drift/);
});
+16 -2
View File
@@ -1,6 +1,8 @@
import assert from 'node:assert/strict';
import {readFileSync, readdirSync, existsSync} from 'node:fs';
import {join} from 'node:path';
import {verifySidebarCoverage} from './sidebar-coverage.mjs';
import {verifyMeasurementPages} from './measurement-pages.mjs';
const read = p => readFileSync(p, 'utf8');
const config = read('docusaurus.config.ts');
assert(config.includes("baseUrl: '/eldorado-v1/documentation/'"));
@@ -16,12 +18,24 @@ const workflow = read('.gitea/workflows/pages.yml');
assert(workflow.includes('mountpoint -q'));
assert(workflow.includes("gitea.event_name == 'push' && gitea.ref == 'refs/heads/main'"));
if (process.argv.includes('--build')) {
await verifySidebarCoverage();
verifyMeasurementPages();
const model = JSON.parse(read('research/ai-adoption/strategy-model.json'));
const indexes = readdirSync('build').filter(f => /^search-index.*\.json$/.test(f)).map(f => read(join('build',f))).join('\n');
for (const {id, title} of model.pages) {
assert(indexes.includes('/eldorado-v1/documentation/strategy/baseline/'), 'Missing indexed Baseline route');
const redirect = read('build/strategy/index.html');
assert(redirect.includes('/eldorado-v1/documentation/strategy/target-operating-model/'));
assert(redirect.includes('window.location.href') && redirect.includes('http-equiv="refresh"') && !redirect.includes('archify-panel'), 'Landing must redirect, not duplicate Target');
const strategyPages = [...model.pages,
{id:'stage-01-skills-adoption', title:'Stage - 01 - Skills Adoption'},
{id:'baseline', title:'Baseline'},
{id:'stage-02-autonomous-agent', title:'Stage - 02 - Autonomous Agent'},
];
for (const {id, title} of strategyPages) {
const route = `strategy/${id === 'index' ? '' : `${id}/`}index.html`;
const page = read(join('build',route));
assert(page.includes(title) && page.includes('Target operating model'), route);
assert(page.includes(title), route);
if (!id.startsWith('stage-')) assert(page.includes('Target operating model'), route);
assert(indexes.includes(title), `Missing indexed Strategy page: ${id}`);
for (const match of page.matchAll(/href="(\/eldorado-v1\/documentation\/[^"?#]*)/g)) {
const local = decodeURIComponent(match[1].replace('/eldorado-v1/documentation/',''));
+10 -1
View File
@@ -1,2 +1,11 @@
import type {SidebarsConfig} from '@docusaurus/plugin-content-docs';
export default {contributionSidebar: ['contribute', 'diagrams']} satisfies SidebarsConfig;
export default {
contributionSidebar: ['contribute', 'diagrams', {
type: 'category', label: 'Portal maintenance', collapsed: true,
items: [
{type: 'link', label: 'Starting point', href: '/eldorado-v1/documentation/docs/overview/'},
{type: 'link', label: 'Update and publish', href: '/eldorado-v1/documentation/docs/maintain/'},
{type: 'link', label: 'Site configuration', href: '/eldorado-v1/documentation/docs/reference/'},
],
}],
} satisfies SidebarsConfig;
+44 -1
View File
@@ -1,2 +1,45 @@
import type {SidebarsConfig} from '@docusaurus/plugin-content-docs';
export default {strategySidebar: ['index', 'target-operating-model', 'skills-governance', 'skills-quality', 'skills-adoption', 'measurement', 'skills-maintenance', 'roadmap']} satisfies SidebarsConfig;
export default {
strategySidebar: [
'target-operating-model',
'roadmap',
{
type: 'category',
label: 'Stage - 01 - Skills Adoption',
link: {type: 'doc', id: 'stage-01-skills-adoption'},
collapsed: true,
items: [
{
type: 'category', label: 'Measurement', collapsed: true,
link: {type: 'doc', id: 'measurement/index'},
items: [
'measurement/validated-task-success',
'measurement/skill-selection-precision',
'measurement/skill-selection-recall',
'measurement/supported-bundle-coverage',
'measurement/approved-workflow-adoption',
'measurement/change-lead-time',
'measurement/deployment-frequency',
'measurement/change-fail-rate',
'measurement/failed-deployment-recovery-time',
'measurement/deployment-rework-rate',
'measurement/changes-with-escaped-quality-issues',
'measurement/confirmed-policy-effects',
'measurement/cost-per-accepted-outcome',
'measurement/verification-confidence-and-cognitive-load',
'measurement/skills-within-substantive-review-window',
'measurement/workflow-specific-business-acceptance',
'measurement/collection-and-safeguards',
'measurement/synthetic-example',
],
},
{type: 'doc', id: 'baseline', label: 'Baseline'},
{type: 'doc', id: 'skills-governance', label: 'Governance'},
{type: 'doc', id: 'skills-quality', label: 'Quality'},
{type: 'doc', id: 'skills-adoption', label: 'Adoption'},
{type: 'doc', id: 'skills-maintenance', label: 'Maintenance'},
],
},
'stage-02-autonomous-agent',
],
} satisfies SidebarsConfig;
+12 -2
View File
@@ -11,6 +11,16 @@ export default function ArchifyDiagram({name, title, compact = false, story = fa
const opener = useRef<HTMLButtonElement>(null);
const headingId = useId();
const [expanded, setExpanded] = useState(false);
const [narrowRoadmap, setNarrowRoadmap] = useState(false);
const skillsStory = /^strategy-(governance|quality|adoption|measurement|baseline|maintenance)$/.test(name);
useEffect(() => {
if (!name.startsWith('strategy-roadmap') && !skillsStory) return;
const media = window.matchMedia(skillsStory ? '(max-width: 1100px)' : '(max-width: 999px)');
const update = () => setNarrowRoadmap(media.matches);
update();
media.addEventListener('change', update);
return () => media.removeEventListener('change', update);
}, [name, skillsStory]);
const {colorMode, setColorMode} = useColorMode();
const initialTheme = useRef(colorMode);
const desktop = useRef<HTMLIFrameElement>(null);
@@ -57,7 +67,7 @@ export default function ArchifyDiagram({name, title, compact = false, story = fa
return () => {document.body.style.overflow = previousOverflow;};
}, [expanded]);
const close = () => {dialog.current?.close();};
return <section className={`archify-panel${compact ? ' archify-panel--compact' : ''}${story ? ' archify-panel--story' : ''}`} data-diagram={name} aria-label={title}>
return <section className={`archify-panel${compact ? ' archify-panel--compact' : ''}${story ? ' archify-panel--story' : ''}${skillsStory ? ' archify-panel--skills' : ''}`} data-diagram={name} aria-label={title}>
<div className="archify-toolbar"><button ref={opener} type="button" className="archify-expand" aria-label={`Expand ${title}`} title="Expand diagram" onClick={() => setExpanded(true)}><svg width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" aria-hidden="true"><path d="M8 3H3v5M16 3h5v5M21 16v5h-5M8 21H3v-5" /></svg></button></div>
{story ? <>
<iframe className="story-desktop" ref={desktop} onLoad={() => syncTheme(desktop.current)} src={`${source}?embed=1&theme=${initialTheme.current}`} title={title} sandbox="allow-scripts allow-downloads" loading="lazy" referrerPolicy="no-referrer" />
@@ -65,7 +75,7 @@ export default function ArchifyDiagram({name, title, compact = false, story = fa
</> : <iframe ref={desktop} onLoad={() => syncTheme(desktop.current)} src={`${source}?theme=${initialTheme.current}`} title={title} sandbox="allow-scripts allow-downloads" loading="lazy" referrerPolicy="no-referrer" />}
<dialog ref={dialog} className="archify-modal" aria-labelledby={headingId} onClose={() => {setExpanded(false); opener.current?.focus();}}>
<div className="archify-modal-toolbar"><strong id={headingId}>{title}</strong><button type="button" onClick={close} autoFocus aria-label="Close full-screen diagram"><span aria-hidden="true">×</span></button></div>
{expanded && <iframe ref={fullscreen} onLoad={() => syncTheme(fullscreen.current)} src={`${source}?theme=${initialTheme.current}`} title={`${title} — expanded`} sandbox="allow-scripts allow-downloads" referrerPolicy="no-referrer" />}
{expanded && <iframe ref={fullscreen} onLoad={() => syncTheme(fullscreen.current)} src={`${narrowRoadmap ? mobileSource : source}?${name.startsWith('strategy-roadmap') || skillsStory ? 'embed=1&' : ''}theme=${initialTheme.current}`} title={`${title} — expanded`} sandbox="allow-scripts allow-downloads" referrerPolicy="no-referrer" />}
</dialog>
</section>;
}
+40 -7
View File
@@ -110,9 +110,13 @@ a:focus-visible, button:focus-visible {outline: 3px solid #b88719; outline-offse
.archify-panel--story {max-width: 740px;}
.archify-panel--story > iframe {height: auto; aspect-ratio: 480 / 408;}
.archify-panel--story > .story-mobile {display: none;}
.archify-panel--story[data-diagram="strategy-target"] > iframe {aspect-ratio: 480 / 628;}
.archify-panel--story[data-diagram="strategy-adoption"] > iframe {aspect-ratio: 545 / 408;}
.archify-panel--story[data-diagram="strategy-maintenance"] > iframe {aspect-ratio: 524 / 408;}
.theme-doc-markdown:has([data-diagram="strategy-roadmap"]) {max-width: none;}
.archify-panel--story[data-diagram^="strategy-roadmap"] {max-width: none; --roadmap-height: 640px;}
.archify-panel--story[data-diagram^="strategy-roadmap"] > .story-desktop {aspect-ratio: auto; height: 300px;}
.archify-panel--story[data-diagram="strategy-roadmap-loop"] {--roadmap-height: 1840px;}
.archify-panel--story[data-diagram="strategy-roadmap-loop"] > .story-desktop {height: 460px;}
.archify-panel--story[data-diagram="strategy-target"] > iframe {aspect-ratio: 1620 / 1430;}
.strategy-content > details {margin: .65rem 0; border: 1px solid var(--line); padding: .8rem 1rem; background: var(--surface);}
.strategy-content summary {cursor: pointer; font-weight: 700;}
.strategy-content summary:focus-visible {outline: 3px solid #b88719; outline-offset: 4px;}
@@ -121,10 +125,14 @@ a:focus-visible, button:focus-visible {outline: 3px solid #b88719; outline-offse
@media (max-width: 700px) {
.archify-panel--story > .story-desktop {display: none;}
.archify-panel--story > .story-mobile {display: block; height: auto; aspect-ratio: 240 / 748;}
.archify-panel--story[data-diagram="strategy-roadmap"] > .story-mobile {aspect-ratio: 240 / 628;}
.archify-panel--story[data-diagram="strategy-adoption"] > .story-mobile {aspect-ratio: 305 / 748;}
.archify-panel--story[data-diagram="strategy-maintenance"] > .story-mobile {aspect-ratio: 284 / 748;}
.archify-panel--story[data-diagram="strategy-target"] > .story-mobile {aspect-ratio: 301 / 868;}
.archify-panel--story[data-diagram="strategy-target"] > .story-mobile {aspect-ratio: 680 / 2340;}
}
/* Keep the three-card loop readable beside the documentation sidebar. */
@media (width < 1100px) {
.archify-panel--story[data-diagram^="strategy-roadmap"] > .story-desktop {display: none;}
.archify-panel--story[data-diagram^="strategy-roadmap"] > .story-mobile {display: block; height: var(--roadmap-height); width: 100%; max-width: 432px; margin-inline: auto; aspect-ratio: auto;}
}
.archify-expand {display: grid; place-items: center; width: 44px; height: 44px; border: 0; padding: 0; background: transparent; color: var(--ifm-link-color); cursor: pointer;}
.archify-expand:hover {background: var(--ifm-hover-overlay);}
@@ -134,4 +142,29 @@ a:focus-visible, button:focus-visible {outline: 3px solid #b88719; outline-offse
.archify-modal-toolbar {display: flex; align-items: center; justify-content: space-between; gap: 16px; padding: 12px 20px; border-bottom: 1px solid var(--line);}
.archify-modal-toolbar button {display: inline-flex; align-items: center; justify-content: center; flex-shrink: 0; width: 44px; height: 44px; padding: 0; background: var(--gold); color: #14131a; font: inherit; font-size: 24px; font-weight: 700; border: 0; cursor: pointer;}
.archify-panel .archify-modal iframe {flex: 1; min-height: 0; height: 100%; width: 100%;}
/* Read narrow Roadmap views by scrolling, never by fitting their
entire height into a short phone screen. Other diagram viewers are unchanged. */
@media (max-width: 999px) {
[data-diagram^="strategy-roadmap"] .archify-modal {overflow-y: auto; overscroll-behavior: contain;}
[data-diagram^="strategy-roadmap"] .archify-modal-toolbar {position: sticky; top: 0; z-index: 1; flex-shrink: 0; background: var(--surface);}
[data-diagram^="strategy-roadmap"] .archify-modal iframe {flex: none; height: var(--roadmap-height); min-height: var(--roadmap-height);}
}
@media (prefers-reduced-motion: reduce) {.start-card {transition: none;} .start-card:hover {transform: none;}}
/* Skills Adoption alone uses the full reading column, not a narrow preview. */
.theme-doc-markdown:has(.archify-panel--skills) {max-width: none;}
.archify-panel--story.archify-panel--skills {max-width: none;}
.archify-panel--skills {--skills-wide: 2000 / 1200; --skills-narrow: 880 / 2900;}
.archify-panel--skills[data-diagram="strategy-governance"] {--skills-wide: 1760 / 1550;}
.archify-panel--skills[data-diagram="strategy-adoption"] {--skills-wide: 2040 / 1300; --skills-narrow: 880 / 2200;}
.archify-panel--skills[data-diagram="strategy-measurement"] {--skills-wide: 2400 / 1280; --skills-narrow: 880 / 2600;}
.archify-panel--skills[data-diagram="strategy-baseline"] {--skills-wide: 2400 / 1280; --skills-narrow: 880 / 2200;}
.archify-panel--skills[data-diagram="strategy-maintenance"] {--skills-wide: 2630 / 1480; --skills-narrow: 880 / 3250;}
.archify-panel--story.archify-panel--skills > .story-desktop {aspect-ratio: var(--skills-wide); height: auto;}
@media (max-width: 1100px) {
.archify-panel--story.archify-panel--skills > .story-desktop {display: none;}
.archify-panel--story.archify-panel--skills > .story-mobile {display: block; aspect-ratio: var(--skills-narrow); height: auto; max-width: 440px; margin-inline: auto;}
.archify-panel--skills .archify-modal {overflow-y: auto; overscroll-behavior: contain;}
.archify-panel--skills .archify-modal-toolbar {position: sticky; top: 0; z-index: 1; flex-shrink: 0; background: var(--surface);}
.archify-panel--skills .archify-modal iframe {flex: none; height: auto; min-height: 0; aspect-ratio: var(--skills-narrow); max-width: 600px; margin-inline: auto;}
}
+1 -1
View File
@@ -25,7 +25,7 @@ export default function Home(): React.ReactElement {
<div className="section-heading"><div><p className="eyebrow">START HERE</p><h2 id="start-title">A clear place to begin.</h2></div><span className="foundation-badge">Foundation · v1</span></div>
<div className="start-grid">
<Link className="start-card" to="/organization/structure/"><span className="card-number">01 / ORGANIZATION</span><h3>Organization</h3><p>Explore the structure workspace and its first interactive diagram.</p><span className="card-action">Explore structure <span aria-hidden="true">↗</span></span></Link>
<Link className="start-card" to="/strategy/"><span className="card-number">02 / STRATEGY</span><h3>Strategy</h3><p>Shape the direction for an AI-powered Eldorado.</p><span className="card-action">View the direction <span aria-hidden="true">↗</span></span></Link>
<Link className="start-card" to="/strategy/target-operating-model/"><span className="card-number">02 / STRATEGY</span><h3>Strategy</h3><p>Shape the direction for an AI-powered Eldorado.</p><span className="card-action">View the direction <span aria-hidden="true">↗</span></span></Link>
<Link className="start-card" to="/contribution/"><span className="card-number">03 / CONTRIBUTION</span><h3>Contribution</h3><p>Contribute evidence, proposals, documentation, and diagrams.</p><span className="card-action">Start contributing <span aria-hidden="true">↗</span></span></Link>
</div>
<aside className="scope-note"><span className="scope-symbol" aria-hidden="true">✦</span><div><strong>Shaping the direction.</strong><p>This space is dedicated to AI strategy and direction for Eldorado. Specific initiatives, priorities, and the roadmap remain to be defined.</p></div></aside>
@@ -0,0 +1,6 @@
<!doctype html>
<html lang="en"><head><meta charset="utf-8"><title>Measurement has moved</title><meta name="robots" content="noindex"><link rel="canonical" href="https://pages.apps.lego-cloud.eu/eldorado-v1/documentation/strategy/measurement/"><script>
const destinations = {"validated-task-success": "/strategy/measurement/validated-task-success/", "skill-selection-precision": "/strategy/measurement/skill-selection-precision/", "skill-selection-recall": "/strategy/measurement/skill-selection-recall/", "supported-bundle-coverage": "/strategy/measurement/supported-bundle-coverage/", "approved-workflow-adoption": "/strategy/measurement/approved-workflow-adoption/", "change-lead-time": "/strategy/measurement/change-lead-time/", "deployment-frequency": "/strategy/measurement/deployment-frequency/", "change-fail-rate": "/strategy/measurement/change-fail-rate/", "failed-deployment-recovery-time": "/strategy/measurement/failed-deployment-recovery-time/", "deployment-rework-rate": "/strategy/measurement/deployment-rework-rate/", "changes-with-escaped-quality-issues": "/strategy/measurement/changes-with-escaped-quality-issues/", "confirmed-policy-effects": "/strategy/measurement/confirmed-policy-effects/", "cost-per-accepted-outcome": "/strategy/measurement/cost-per-accepted-outcome/", "verification-confidence-and-cognitive-load": "/strategy/measurement/verification-confidence-and-cognitive-load/", "skills-within-substantive-review-window": "/strategy/measurement/skills-within-substantive-review-window/", "workflow-specific-business-acceptance": "/strategy/measurement/workflow-specific-business-acceptance/", "collection-and-safeguards": "/strategy/measurement/collection-and-safeguards/", "decide-what-counts-before-counting": "/strategy/measurement/collection-and-safeguards/#decide-what-counts-before-counting", "baseline-and-interpretation": "/strategy/measurement/collection-and-safeguards/#baseline-and-interpretation", "event-and-privacy-contract": "/strategy/measurement/collection-and-safeguards/#event-and-privacy-contract", "run-the-synthetic-measurement-example": "/strategy/measurement/synthetic-example/", "metric-contracts": "/strategy/measurement/#metric-definitions"};
const anchor = window.location.hash.slice(1);
window.location.replace("/eldorado-v1/documentation" + (Object.hasOwn(destinations, anchor) ? destinations[anchor] : "/strategy/measurement/"));
</script><noscript><meta http-equiv="refresh" content="0;url=/eldorado-v1/documentation/strategy/measurement/"></noscript></head><body><a href="/eldorado-v1/documentation/strategy/measurement/">Continue to Skills Measurement</a></body></html>