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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
72 changed files with 4565 additions and 1314 deletions

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"icon": "none"
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{
"id": "promote",
"type": "security",
"label": "Promote or hold",
"sublabel": "Owner decision",
"id": "accept",
"type": "backend",
"label": "Accept evidence",
"tag": "All mandatory gates passed",
"sublabel": "Proceed to scoped approval",
"pos": [
260,
280
1430,
160
],
"size": [
180,
60
]
510,
190
],
"icon": "none"
},
{
"id": "rework",
"type": "security",
"label": "Rework / retest",
"tag": "Any failure or missing evidence",
"sublabel": "Keep failures in the record",
"pos": [
1430,
760
],
"size": [
510,
190
],
"icon": "none"
}
],
"connections": [
{
"id": "flow-0",
"from": "risk",
"to": "plan",
"label": "Scope"
},
{
"id": "flow-1",
"from": "plan",
"to": "trial",
"label": "freeze plan"
},
{
"id": "flow-2",
"from": "trial",
"to": "verify",
"label": "Assess"
},
{
"id": "flow-3",
"from": "verify",
"id": "selection-gate",
"from": "selection",
"to": "gate",
"label": "review evidence"
"label": "",
"fromSide": "right",
"toSide": "left",
"route": "straight",
"width": 4,
"variant": "default",
"via": [
[
650,
155
],
[
650,
505
]
]
},
{
"id": "flow-4",
"id": "safety-gate",
"from": "safety",
"to": "gate",
"label": "",
"fromSide": "right",
"toSide": "left",
"route": "straight",
"width": 4,
"variant": "default",
"via": [
[
650,
395
],
[
650,
505
]
]
},
{
"id": "artifact-gate",
"from": "artifact",
"to": "gate",
"label": "",
"fromSide": "right",
"toSide": "left",
"route": "straight",
"width": 4,
"variant": "default",
"via": [
[
650,
635
],
[
650,
505
]
]
},
{
"id": "outcome-gate",
"from": "outcome",
"to": "gate",
"label": "",
"fromSide": "right",
"toSide": "left",
"route": "straight",
"width": 4,
"variant": "default",
"via": [
[
650,
875
],
[
650,
505
]
]
},
{
"id": "gate-accept",
"from": "gate",
"to": "promote",
"label": "decide"
"to": "accept",
"label": "Pass",
"fromSide": "right",
"toSide": "left",
"route": "straight",
"width": 4,
"variant": "default",
"via": [
[
1340,
505
],
[
1340,
255
]
],
"labelAt": [
1330,
210
]
},
{
"id": "gate-rework",
"from": "gate",
"to": "rework",
"label": "Fail",
"fromSide": "right",
"toSide": "left",
"route": "straight",
"width": 4,
"variant": "security",
"via": [
[
1340,
505
],
[
1340,
855
]
],
"labelAt": [
1325,
900
]
}
]
}
}
+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
+56
View File
@@ -0,0 +1,56 @@
---
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
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.
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>
-71
View File
@@ -1,71 +0,0 @@
---
id: measurement
title: Skills Measurement
sidebar_label: Skills Measurement
description: Which KPIs to collect during skills adoption, where the evidence comes from, how to calculate them and when to report.
hide_table_of_contents: true
---
import ArchifyDiagram from '@site/src/components/ArchifyDiagram';
<div className="strategy-content">
Measure adoption in stages: first establish today’s performance, then follow the pilot, extend coverage and keep skills current. Count use separately from outcomes—more use does not by itself mean better work.
<ArchifyDiagram name="strategy-measurement" title="Skills adoption measurement: baseline, pilot, broader adoption and monitoring" story />
**Recommended collection plan · Target operating model, not installed telemetry.** Confirm the proposed roles and reporting cadence below before collecting data.
## 1. Establish the baseline
Choose one workflow, such as reviewing a code change with a review skill. Agree what counts as a started task, independent acceptance and the follow-up period before counting outcomes. Collect current-practice evidence over a complete comparable workflow cycle and until the agreed sample requirement is met; use the same rules in the pilot.
Start with a controlled worksheet or export. Join task IDs to acceptance records, PR/commit IDs, CI results and later defects. Record the exact skill revision and client configuration for pilot work; keep missing versions unknown. Repository and CI evidence support verification, but a green build alone is not task acceptance.
## 2. Measure the pilot
Start with these four questions. Capture inputs as work happens; do not reconstruct review effort from elapsed PR time.
### Are tasks reaching acceptance?
**Collect:** task starts and independent acceptance, failure or abandonment records from the work tracker. **Calculate:** accepted tasks / all eligible starts whose observation period has ended × 100. Failed, abandoned and unresolved tasks stay in the denominator; show unknown outcomes and coverage separately. This is [validated task success](./reference/measurement-contracts.mdx#validated-task-success), not a count of agent completions. **Weekly:** Quality Engineering reviews the pilot cohort.
### Is quality holding up?
**Collect:** accepted change IDs, linked confirmed defects, severity and follow-up dates from review and defect records; retain PR/CI evidence. **Calculate:** changes with at least one confirmed defect / accepted changes with completed follow-up × 100. Count each affected change once, not each defect. Missing links do not mean clean work. **Monthly:** Quality Engineering reviews [escaped quality](./reference/measurement-contracts.mdx#changes-with-escaped-quality-issues) after follow-up, alongside severe incident counts.
### What does an accepted outcome cost?
**Collect:** invoices and usage costs plus sampled human review/rework minutes at approved rates, including unsuccessful attempts and allocated licenses/tooling. **Calculate:** total allocated workflow cost / independently accepted tasks in the same matured start cohort. Keep effort separate from waiting time. Missing buckets make this a partial estimate, not total cost. **Monthly:** Finance & Accounting reconciles [cost per accepted outcome](./reference/measurement-contracts.mdx#cost-per-accepted-outcome), restating late invoices.
### Can people confidently verify the work?
**Collect:** an anonymous 1–5 survey after a pilot workflow cycle: verification confidence, manageable workload and usefulness as separate items. **Calculate:** sum of valid confidence scores / valid responses; also show the distribution and responses / invitations × 100. This guides enablement, not claims of saved time. **After each pilot cycle:** People & Administration reviews [confidence and cognitive load](./reference/measurement-contracts.mdx#verification-confidence-and-cognitive-load); protect small groups.
### 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%**. The report calls for reconciling the unknown task and missing costs, not claiming a skills benefit. Reproduce it with `node scripts/ai-kpi.mjs`; [fixture and limits](./reference/measurement-contracts.mdx#run-the-synthetic-measurement-example).
## 3. Extend collection as adoption grows
Keep those outcome measures, then add reach. An adoption percentage is meaningless without a known eligible population.
**Are supported skills available?** Freeze the expected active installation inventory; compare observed bundle/adapter revisions with the approved support and revocation records. [Supported bundle coverage](./reference/measurement-contracts.mdx#supported-bundle-coverage) = fresh, verified supported installations / all expected active installations × 100. Offline or stale entries stay in the denominator. **Weekly and at revocation:** Platform & IT reconciles coverage.
**Are approved workflows being used?** Freeze the lawfully enrolled participant cohort; collect workflow-linked use of an approved revision through a qualified adapter or a separately labeled declaration. [Approved-workflow adoption](./reference/measurement-contracts.mdx#approved-workflow-adoption) = eligible participants with at least one observed approved use / eligible invited participants × 100. Report this as an observed lower bound with source coverage: missing use is unknown. Installation and loading are not use. **Monthly:** Data & AI reviews reach without invocation quotas or employee rankings.
## 4. Keep the collection running
**Are skills still maintained?** From the versioned catalog, join each active approved revision to its owner, substantive review evidence and due date. [Review coverage](./reference/measurement-contracts.mdx#skills-within-substantive-review-window) = revisions with all three current / all active approved revisions × 100. **Monthly and each release:** Data & AI reports overdue/ownerless revisions and deprecated or revoked versions still in use—not just a percentage.
At each report, compare like workflows with the baseline and publish the period, counts, exclusions and source coverage. Zero denominators mean “not available.” Trends are descriptive, not causal ROI. Act on critical policy effects immediately; add selection precision/recall at qualification and service-level delivery or departmental outcome measures when their source links are ready.
Agree purpose, lawful basis, access and retention first. No raw prompts, code or secrets by default; suppress people cohorts below five and prevent identifying drill-downs.
[Full KPI reference →](./reference/measurement-contracts.mdx) preserves all definitions, collection safeguards and the distinction between synthetic calculations and unimplemented metrics.
**Next:** [Maintain skills using the evidence →](./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>
+57
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@@ -0,0 +1,57 @@
---
id: index
slug: /measurement
title: Skills Measurement
sidebar_label: Measurement
description: Registry of available candidate KPIs and metrics, their applicability, evidence requirements, calculations and limitations.
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">
Browse available candidate KPIs and metrics. Registry inclusion does not require a metric to be used, collected or baselined. Count use separately from outcomes—more use does not by itself mean better work.
<ArchifyDiagram name="strategy-measurement" title="An optional metric registry: browse distinct questions and inspect each contract" 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. Selection measures concern qualification; coverage and adoption concern reach; DORA measures concern service delivery. Outcome, safety, cost, experience and maintenance measures retain their distinct 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.
1. [Validated task success](./validated-task-success.mdx) — prototype calculation
2. [Skill selection precision](./skill-selection-precision.mdx) — prototype calculation
3. [Skill selection recall](./skill-selection-recall.mdx) — prototype calculation
4. [Supported bundle coverage](./supported-bundle-coverage.mdx) — unimplemented metric
5. [Approved-workflow adoption](./approved-workflow-adoption.mdx) — unimplemented metric
6. [Change lead time](./change-lead-time.mdx) — unimplemented metric
7. [Deployment frequency](./deployment-frequency.mdx) — unimplemented metric
8. [Change fail rate](./change-fail-rate.mdx) — prototype calculation
9. [Failed deployment recovery time](./failed-deployment-recovery-time.mdx) — unimplemented metric
10. [Deployment rework rate](./deployment-rework-rate.mdx) — prototype calculation
11. [Changes with escaped quality issues](./changes-with-escaped-quality-issues.mdx) — prototype calculation
12. [Confirmed policy effects](./confirmed-policy-effects.mdx) — prototype calculation
13. [Cost per accepted outcome](./cost-per-accepted-outcome.mdx) — prototype calculation
14. [Verification confidence and cognitive load](./verification-confidence-and-cognitive-load.mdx) — prototype calculation
15. [Skills within substantive review window](./skills-within-substantive-review-window.mdx) — unimplemented metric
16. [Workflow-specific business acceptance](./workflow-specific-business-acceptance.mdx) — unimplemented metric
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 +1,36 @@
---
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 */}
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>
@@ -1,363 +0,0 @@
---
id: measurement-contracts
title: Skills KPI reference
description: Full KPI contracts, minimal events, illustrative calculations, privacy and limits.
---
<div className="strategy-content">
Return to the [Skills Measurement collection plan](../measurement.mdx).
**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.
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.
## Collection and safeguards
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.
## 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. |
## 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%. 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.
**Next:** [Use findings to maintain, quarantine or replace skills →](../skills-maintenance.mdx)
</div>
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@@ -33,7 +33,7 @@ Repeat this loop within every phase—not as six global roadmap stages. Skills t
**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.mdx) explains collection and calculation. Connect reviewed skills to the engineering path, with clear triggers, dependencies and acceptance checks.
**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.
@@ -68,6 +68,6 @@ Stage 2 builds on proven skills, measurements and working practices—not permis
</details>
**Next:** [Return to the strategy destination →](./target-operating-model.mdx)
**Next:** [Stage - 01 - Skills Adoption →](./stage-01-skills-adoption.mdx)
</div>
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@@ -36,6 +36,36 @@ 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
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>
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@@ -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.
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) — browse available candidate metrics; inclusion does not require collection or baselining.
- [Baseline](./baseline.mdx) — understand a workflow, select relevant metrics and record feasible starting evidence or explicit gaps.
- [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) — coach bounded workflows with a supported client and a manual path.
- [Maintenance](./skills-maintenance.mdx) — review feedback, 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>
+2 -2
View File
@@ -157,11 +157,11 @@ Success means accepted outcomes with maintained quality, controlled risk and und
- [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.
- [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:** [Decide who owns and approves each skill →](./skills-governance.mdx)
**Next:** [Follow the Roadmap toward Target →](./roadmap.mdx)
</div>
+1 -1
View File
@@ -15,7 +15,7 @@
"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 && 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",
"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": {
@@ -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"
}
]
}
+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)'));
});
+2 -2
View File
@@ -125,9 +125,9 @@ const fs = require('node:fs');
await page.screenshot({path:`${output}/${width}.png`, fullPage:true});
await frame.locator('#btn-theme').click(); await theme('dark');
// Exercise keyboard navigation without racing the portal's smooth scroll.
await page.locator('.strategy-content a[href$="/strategy/skills-governance/"]').filter({visible:true}).focus();
await page.locator('.strategy-content a[href$="/strategy/roadmap/"]').filter({visible:true}).focus();
await page.keyboard.press('Enter');
await page.waitForURL('**/strategy/skills-governance/');
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();
+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(`${output}/results.json`,JSON.stringify(results,null,2));
console.log('PASS: 16 metric pages × 2 widths; canonical metadata, contract fields, status, all legacy metric/shared/fallback redirects and linked Measurement keyboard navigation');
} finally {await browser.close();}
})().catch(e => {console.error(e);process.exitCode=1;});
+1 -1
View File
@@ -23,7 +23,7 @@ const fs = require('node:fs');
if (width < 700) await page.getByRole('button', {name:'Toggle navigation bar'}).click();
const menu = page.locator('.theme-doc-sidebar-menu .menu__link').filter({visible:true});
await menu.first().waitFor({state:'visible'});
assert.deepEqual(await menu.allTextContents(), ['Target', 'Roadmap', 'Skills governance', 'Skills quality', 'Skills adoption', 'Skills Measurement', 'Skills maintenance']);
assert.deepEqual(await menu.allTextContents(), ['Target', 'Roadmap', 'Stage - 01 - Skills Adoption', 'Stage - 02 - Autonomous Agent']);
assert((await menu.nth(0).getAttribute('href')).endsWith('/strategy/target-operating-model/'));
assert((await menu.nth(1).getAttribute('href')).endsWith('/strategy/roadmap/'));
assert.equal(await menu.filter({hasText:/^Target$/}).count(), 1);
+61
View File
@@ -0,0 +1,61 @@
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 ${documents.length} docs have visible unique sidebar entries at 3 viewports; Contribution links, Measurement breadcrumbs and reported anchor redirect work`);
} finally {await browser.close();}
})().catch(e => {console.error(e); process.exitCode = 1;});
+45
View File
@@ -0,0 +1,45 @@
const {chromium}=require('playwright');
const fs=require('node:fs');
const path=require('node:path');
const assert=require('node:assert/strict');
(async()=>{
const dir=process.argv[2]||'.cache/skills-candidate';
const browser=await chromium.launch({executablePath:process.env.PLAYWRIGHT_CHROMIUM_EXECUTABLE,args:['--no-sandbox']});
const results=[];
try {
for(const topic of ['measurement','baseline','governance','quality','adoption','maintenance']) for(const width of [1440,1024,390,320]){
const spec=JSON.parse(fs.readFileSync(`diagrams/strategy-${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});
+8 -8
View File
@@ -18,11 +18,12 @@ const fs = require('node:fs');
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(), 4);
assert.equal(await page.locator('.strategy-content h2').count(), 2);
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','Skills governance','Skills quality','Skills adoption','Skills Measurement','Skills maintenance']);
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');
@@ -33,7 +34,7 @@ const fs = require('node:fs');
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, 6);
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: ${geometry.minLabel}`);
await frame.locator('#btn-theme').click();
@@ -50,7 +51,7 @@ const fs = require('node:fs');
assert.equal(await download.failure(), null);
const path = `${output}/${width}.svg`; await download.saveAs(path);
const svg = fs.readFileSync(path, 'utf8');
assert(svg.includes('Establish baseline') && svg.includes('Ongoing monitoring'));
assert(svg.includes('Available choices') && svg.includes('No mandatory collection'));
const opener = panel.getByRole('button', {name:/^Expand /});
await opener.click();
const close = panel.getByRole('button', {name:'Close full-screen diagram', exact:true});
@@ -65,21 +66,20 @@ const fs = require('node:fs');
await page.locator('.strategy-content h2').nth(1).scrollIntoViewIfNeeded();
await page.screenshot({path:`${output}/${width}-pilot.png`});
await page.screenshot({path:`${output}/${width}-full.png`, fullPage:true});
const links = await page.locator('.strategy-content a[href*="measurement-contracts"]').evaluateAll(nodes => nodes.map(n => n.href));
const links = await page.locator('.strategy-content a[href*="/measurement/"]').evaluateAll(nodes => nodes.map(n => n.href));
for (const href of [...new Set(links)]) {
const navigation = await page.goto(href, {waitUntil:'networkidle'});
if (navigation) assert.equal(navigation.status(), 200);
assert.equal(page.url(), href);
if (new URL(href).hash) await page.locator(new URL(href).hash).waitFor({state:'visible'});
}
assert.equal(await page.locator('.strategy-content h3').count(), 19);
assert((await page.locator('.strategy-content').innerText()).includes('9 prototype calculations and 7 unimplemented metrics'));
assert.equal(new Set(links.map(h => new URL(h).pathname)).size, 18);
assert(!await page.evaluate(() => document.documentElement.scrollWidth > innerWidth));
assert.deepEqual(errors, []);
results.push({width, geometry, links:links.length, title:true, sidebar:true, controls:true, export:true, reference:true});
fs.writeFileSync(`${output}/results.json`, JSON.stringify(results,null,2));
await context.close();
}
console.log(`PASS ${results.length} Skills Measurement viewports: title/sidebar, open plan, diagram geometry/controls/export, all reference links and no page errors`);
console.log(`PASS ${results.length} Skills Measurement viewports: title/sidebar, optional registry, diagram geometry/controls/export, all reference links and no page errors`);
} finally {await browser.close();}
})().catch(error => {console.error(error); process.exitCode = 1;});
+58
View File
@@ -0,0 +1,58 @@
const {chromium}=require('playwright');
const fs=require('node:fs');
const assert=require('node:assert/strict');
(async()=>{
const base=process.argv[2]||'http://127.0.0.1:4173';
const out=`.cache/skills-${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();
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 ${ids.length} routes; linked Measurement category, keyboard expansion, breadcrumbs, next/previous and no overflow/errors`);
} finally {await browser.close();}
})().catch(error => {console.error(error); process.exitCode = 1;});
+6 -3
View File
@@ -19,10 +19,12 @@ const fs=require('node:fs');
const nodes=[...svg.querySelectorAll('[data-node-id]')].map(n=>{const r=n.getBoundingClientRect();return {id:n.id,x:r.x,y:r.y,right:r.right,bottom:r.bottom};});
return {width:innerWidth,height:innerHeight,nodes,svg:svg.getBoundingClientRect().toJSON(),minLabel:Math.min(...[...svg.querySelectorAll('text[data-node-label]')].map(n=>parseFloat(getComputedStyle(n).fontSize)*n.getScreenCTM().a))};
});
assert(geometry.nodes.length>=(id==='roadmap'?2:5) && geometry.nodes.length<=(['index','target-operating-model'].includes(id)?18:7),id);
const name=await panel.getAttribute('data-diagram');
const source=JSON.parse(fs.readFileSync(`diagrams/${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)} / ${geometry.height}`);
const data=await page.locator('.strategy-content').evaluate(el=>({words:el.innerText.trim().split(/\s+/).length,overflow:document.documentElement.scrollWidth>innerWidth,openDetails:el.querySelectorAll('details[open]').length}));
assert(data.words<=(id==='measurement'?1100:id==='roadmap'?600:200),id);assert(!data.overflow,id);assert.equal(data.openDetails,0,id);
assert(data.words<=(id==='measurement'?1500:id==='roadmap'?600:200),id);assert(!data.overflow,id);assert.equal(data.openDetails,0,id);
await page.evaluate(()=>scrollTo({top:0,behavior:'instant'}));await page.screenshot({path:`.cache/story-${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'});
@@ -42,7 +44,8 @@ const fs=require('node:fs');
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/reference/measurement-contracts/#validated-task-success`,{waitUntil:'networkidle'});
const heading=page.locator('#validated-task-success');await heading.waitFor({state:'visible'});
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();
}
+8 -6
View File
@@ -1,6 +1,7 @@
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';
@@ -27,11 +28,12 @@ for (const file of readdirSync('diagrams').sort()) {
if (spec.diagram_type !== type || spec.meta.output !== output) throw new Error(`Diagram type/output mismatch: ${file}`);
const run = args => execFileSync(process.execPath,[cli,...args],{stdio:'inherit',env:{...process.env,ARCHIFY_UPDATE_CHECK_DISABLED:'1'}});
const roadmap = /^strategy-roadmap(?:-(?:adoption|loop))?(?:-mobile)?$/.test(name);
if (roadmap) {
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/workflow/render-workflow.mjs', input, output], {stdio:'inherit', env:{...process.env, ARCHIFY_UPDATE_CHECK_DISABLED:'1'}});
writeFileSync(output, roadmapViewer(readFileSync(output, 'utf8'), spec));
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']);
@@ -61,13 +63,13 @@ for (const file of readdirSync('diagrams').sort()) {
}
writeFileSync(output, viewer.replace('</head>', `<style id="eldorado-inline-controls">${inlineStyles}</style><style id="eldorado-cycle-labels">${storyStyles}</style></head>`)
.replace('</body>', `<script>${themeBridge}</script></body>`));
if (roadmap) {
if (roadmap || skills) {
// This is a portal receipt, not upstream deliver provenance: formatting
// happens between the native schema/layout compiler and artifact checker.
const hash = path => createHash('sha256').update(readFileSync(path)).digest('hex');
const checked = JSON.parse(execFileSync(process.execPath, [cli,'check',output,'--json'], {encoding:'utf8', env:{...process.env, ARCHIFY_UPDATE_CHECK_DISABLED:'1'}}));
if (!checked.ok || checked.composition?.status !== 'pass') throw new Error('Roadmap final artifact failed');
writeFileSync(`.cache/archify/${name}.portal.json`, JSON.stringify({source:input, sourceSha256:hash(input), adapterSha256:hash('scripts/roadmap-viewer.mjs'), artifactSha256:hash(output), checker:checked}, null, 2));
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/${name}.delivery.json`);
if (name === 'strategy-target') {
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import assert from 'node:assert/strict';
import {readFileSync, readdirSync} from 'node:fs';
import {runInNewContext} from 'node:vm';
const read = p => readFileSync(p, 'utf8');
export function verifyMeasurementPages() {
const manifest = JSON.parse(read('research/ai-adoption/measurement-migration.json'));
const {documents, exclusions} = JSON.parse(read('.cache/sidebar-coverage.json'));
const prefix = '/eldorado-v1/documentation';
const legacy = 'strategy/reference/measurement-contracts/index.html';
assert.equal(exclusions.filter(e => e.file === legacy).length, 1);
assert(!documents.some(d => d.id === 'reference/measurement-contracts'));
const search = readdirSync('build').filter(f => /^search-index.*\.json$/.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');
}
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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);
}
});
+1 -1
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@@ -13,7 +13,7 @@ test('Roadmap has three visual levels and preserves human direction and Delivery
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.mdx', './target-operating-model.mdx']) assert(visible.includes(marker), marker);
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));
});
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@@ -5,7 +5,7 @@ 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: \['target-operating-model', 'roadmap'/);
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`);
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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);
});
+12 -9
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@@ -4,21 +4,24 @@ import {readFileSync} from 'node:fs';
import {calculate} from './ai-kpi.mjs';
const read = path => readFileSync(path, 'utf8');
test('Skills Measurement is an open adoption collection plan, not a hidden catalogue', () => {
const page = read('docs/strategy/measurement.mdx');
assert.match(page, /title: Skills Measurement\nsidebar_label: Skills 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);
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('./reference/measurement-contracts.mdx'));
assert(page.includes('./collection-and-safeguards.mdx'));
assert(!page.includes('Is AI-assisted work worth continuing?'));
for (const word of ['Recommended', 'not installed', 'unknown', 'review', 'CI', 'revision', 'Monthly', 'Weekly']) assert(page.includes(word), word);
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 page = read('docs/strategy/reference/measurement-contracts.mdx');
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 = 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 ['Numerator','Denominator','Expression','Aggregation','Unit','Eligible population','Exclusions','Events and source','Owner / cadence','Missing evidence','Gaming and limits']) assert(section.includes(`| ${field} |`));
}
@@ -26,7 +29,7 @@ test('all sixteen metric definitions remain in the reference with explicit imple
});
test('published pilot arithmetic matches the executable fixture, including partial cost', () => {
const page = read('docs/strategy/measurement.mdx');
const page = read('docs/strategy/skills-adoption.mdx');
const fixture = JSON.parse(read('scripts/fixtures/ai-kpi-synthetic.json'));
const report = calculate(fixture);
const success = report.kpis['validated-task-success'];
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import {test} from 'node:test';
import assert from 'node:assert/strict';
import {readFileSync, mkdtempSync, rmSync} from 'node:fs';
import {tmpdir} from 'node:os';
import {join} from 'node:path';
import {execFileSync} from 'node:child_process';
import {skillsViewer,isSkillsStory} from './skills-viewer.mjs';
const read = p => readFileSync(p,'utf8');
const topics = ['measurement','baseline','governance','quality','adoption','maintenance'];
test('all seven Skills Adoption pages account for six diagrams and twelve sources',()=>{
let count=0;
for(const route of ['stage-01-skills-adoption',...topics.map(t=>['measurement','baseline'].includes(t)?t:`skills-${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-${t}.architecture.json`)));
assert(text('governance').includes('Author is not sole approver'));
assert(text('quality').includes('Critical effect blocks'));
assert(text('adoption').includes('Delivery first')&&text('adoption').includes('Later order undecided'));
assert(text('adoption').includes('No quotas or rankings'));
for(const marker of ['Available choices','16 candidate contracts','No mandatory collection','Meaning + applicability','9 prototype / 7 unimplemented'])assert(text('measurement').includes(marker),marker);
assert(text('maintenance').includes('No automatic reinstatement'));
});
test('topic compositions explain distinct relationships rather than a fixed card count',()=>{
const spec=t=>JSON.parse(read(`diagrams/strategy-${t}.architecture.json`));
const has=(d,a,b)=>assert(d.connections.some(e=>e.from===a&&e.to===b),`${a} → ${b}`);
const g=spec('governance');const steps=g.components.filter(n=>/^0[1-6]/.test(n.label));
assert.equal(steps.length,6);
for(let i=1;i<steps.length;i++){assert(steps[i].pos[0]>steps[i-1].pos[0]);assert(steps[i].pos[1]>steps[i-1].pos[1]);has(g,steps[i-1].id,steps[i].id);}
has(g,'approve','owner');has(g,'distribute','withdraw');
const q=spec('quality');for(const id of ['selection','safety','artifact','outcome'])has(q,id,'gate');has(q,'gate','accept');has(q,'gate','rework');
const a=spec('adoption');for(const [x,y] of [['human','agent'],['agent','human'],['agent','learn'],['learn','delivery'],['learn','expand'],['human','expand']])has(a,x,y);
const m=spec('measurement');for(const id of ['qualification','outcomes','experience','health']){has(m,'registry',id);has(m,id,'contract');}
const b=spec('baseline');for(const [x,y] of [['workflow','selection'],['selection','evidence'],['evidence','position'],['position','comparison']])has(b,x,y);
const c=spec('maintenance');for(const [x,y] of [['observe','triage'],['triage','change'],['change','validate'],['validate','release'],['release','observe'],['triage','safe'],['safe','observe'],['triage','retire'],['triage','contain'],['contain','change']])has(c,x,y);
});
+44
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@@ -0,0 +1,44 @@
// Native editable geometry and edges; scoped editorial typography for Stage 01.
export const isSkillsStory = name => /^strategy-(governance|quality|adoption|measurement|baseline|maintenance)(-mobile)?$/.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;
}
+39 -5
View File
@@ -1,17 +1,51 @@
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 one canonical Target, then Roadmap, without a landing menu duplicate', () => {
const sidebar = read('sidebars/strategy.ts').split('strategySidebar: [')[1].split(']')[0];
const ids = [...sidebar.matchAll(/'([^']+)'/g)].map(match => match[1]);
assert.deepEqual(ids, ['target-operating-model', 'roadmap', 'skills-governance', 'skills-quality', 'skills-adoption', 'measurement', 'skills-maintenance']);
assert.equal(ids.filter(id => id === 'target-operating-model').length, 1);
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$/m);
});
test('old Strategy entry redirects to Target instead of maintaining a second document', () => {
assert(!existsSync('docs/strategy/index.mdx'));
assert.match(read('docusaurus.config.ts'), /'@docusaurus\/plugin-client-redirects'/);
+11 -11
View File
@@ -6,25 +6,25 @@ const model = JSON.parse(read('research/ai-adoption/strategy-model.json'));
test('every strategy page leads with a compact diagram story and closes its references', () => {
for (const {id} of model.pages) {
const page = read(`docs/strategy/${id}.mdx`);
const page = read(`docs/strategy/${id === 'measurement' ? 'measurement/index' : id}.mdx`);
const narrative = page.split('<div className="strategy-content">')[1].replace(/<details>[\s\S]*?<\/details>/g, '');
assert.equal((narrative.match(/<ArchifyDiagram /g) || []).length, id === 'roadmap' ? 3 : 1, id);
assert(narrative.includes(' story />'), id);
assert(!page.includes('<details>') || page.indexOf(' story />') < page.indexOf('<details>'), id);
assert(!/<details\s+open/.test(page), id);
assert.equal((page.match(/<details>/g) || []).length, (page.match(/<\/details>/g) || []).length, id);
assert.equal((narrative.match(/^## /gm) || []).length, id === 'measurement' ? 4 : id === 'roadmap' ? 4 : 1, id);
assert.equal((narrative.match(/^## /gm) || []).length, id === 'measurement' ? 2 : id === 'roadmap' ? 4 : 1, id);
assert((narrative.match(/^- /gm) || []).length <= 3, id);
assert(narrative.includes('**Next:**'), id);
assert(!narrative.includes('| ---'), id);
const words = narrative.replace(/<[^>]*>/g, '').trim().split(/\s+/).length;
assert(words <= (id === 'measurement' ? 1100 : id === 'roadmap' ? 600 : 200), `${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`));
@@ -35,21 +35,21 @@ test('mobile story diagrams preserve the same nodes and directed relationships',
}
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 <= (name === 'strategy-target' ? 18 : 7), name);
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.id.startsWith('govern-')) && 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 linked reference', () => {
assert(read('docs/strategy/measurement.mdx').includes('./reference/measurement-contracts.mdx'));
const page = read('docs/strategy/reference/measurement-contracts.mdx');
const contracts = page.split('## Metric contracts')[1].split('## Run the synthetic')[0];
assert.equal((contracts.match(/^### /gm) || []).length, 16);
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}: ${label}`);
}
+9 -8
View File
@@ -3,15 +3,16 @@ import assert from 'node:assert/strict';
import {readFileSync, readdirSync} from 'node:fs';
const read = p => readFileSync(p, 'utf8');
const model = JSON.parse(read('research/ai-adoption/strategy-model.json'));
test('seven canonical strategy pages preserve target boundary and separate evidence', () => {
test('seven existing strategy pages and two stage overviews preserve canonical routes', () => {
assert.equal(model.pages.length, 7);
assert.equal(readdirSync('docs/strategy').filter(p => p.endsWith('.mdx')).length, 7);
assert.deepEqual(readdirSync('docs/strategy').filter(p => p.endsWith('.mdx')).sort(),
[...model.pages.filter(p => p.id !== 'measurement').map(({id}) => `${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('seven canonical strategy pages preserve target boundary and separate evide
}
});
test('every metric has an actionable reader-facing contract', () => {
const page = read('docs/strategy/reference/measurement-contracts.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(`| ${field} |`));
assert(section.includes(k.owner));
}
assert(page.includes('synthetic') && page.includes('not a production ingestion system'));
assert(read('docs/strategy/measurement/synthetic-example.mdx').includes('not a production ingestion system'));
});
test('diagram preserves independent release approval and no agent production authority', () => {
const d=JSON.parse(read('diagrams/ai-adoption-target.architecture.json'));
+13 -2
View File
@@ -1,6 +1,8 @@
import assert from 'node:assert/strict';
import {readFileSync, readdirSync, existsSync} from 'node:fs';
import {join} from 'node:path';
import {verifySidebarCoverage} from './sidebar-coverage.mjs';
import {verifyMeasurementPages} from './measurement-pages.mjs';
const read = p => readFileSync(p, 'utf8');
const config = read('docusaurus.config.ts');
assert(config.includes("baseUrl: '/eldorado-v1/documentation/'"));
@@ -16,15 +18,24 @@ const workflow = read('.gitea/workflows/pages.yml');
assert(workflow.includes('mountpoint -q'));
assert(workflow.includes("gitea.event_name == 'push' && gitea.ref == 'refs/heads/main'"));
if (process.argv.includes('--build')) {
await verifySidebarCoverage();
verifyMeasurementPages();
const model = JSON.parse(read('research/ai-adoption/strategy-model.json'));
const indexes = readdirSync('build').filter(f => /^search-index.*\.json$/.test(f)).map(f => read(join('build',f))).join('\n');
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');
for (const {id, title} of model.pages) {
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: ['target-operating-model', 'roadmap', 'skills-governance', 'skills-quality', 'skills-adoption', 'measurement', 'skills-maintenance']} 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;
+6 -5
View File
@@ -12,14 +12,15 @@ export default function ArchifyDiagram({name, title, compact = false, story = fa
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')) return;
const media = window.matchMedia('(max-width: 999px)');
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]);
}, [name, skillsStory]);
const {colorMode, setColorMode} = useColorMode();
const initialTheme = useRef(colorMode);
const desktop = useRef<HTMLIFrameElement>(null);
@@ -66,7 +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=${initialTheme.current}`} title={title} sandbox="allow-scripts allow-downloads" loading="lazy" referrerPolicy="no-referrer" />
@@ -74,7 +75,7 @@ export default function ArchifyDiagram({name, title, compact = false, story = fa
</> : <iframe ref={desktop} onLoad={() => syncTheme(desktop.current)} src={`${source}?theme=${initialTheme.current}`} title={title} sandbox="allow-scripts allow-downloads" loading="lazy" referrerPolicy="no-referrer" />}
<dialog ref={dialog} className="archify-modal" aria-labelledby={headingId} onClose={() => {setExpanded(false); opener.current?.focus();}}>
<div className="archify-modal-toolbar"><strong id={headingId}>{title}</strong><button type="button" onClick={close} autoFocus aria-label="Close full-screen diagram"><span aria-hidden="true">×</span></button></div>
{expanded && <iframe ref={fullscreen} onLoad={() => syncTheme(fullscreen.current)} src={`${narrowRoadmap ? mobileSource : source}?${name.startsWith('strategy-roadmap') ? 'embed=1&' : ''}theme=${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>;
}
+20 -4
View File
@@ -116,8 +116,7 @@ a:focus-visible, button:focus-visible {outline: 3px solid #b88719; outline-offse
.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;}
.archify-panel--story[data-diagram="strategy-adoption"] > iframe {aspect-ratio: 545 / 408;}
.archify-panel--story[data-diagram="strategy-maintenance"] > iframe {aspect-ratio: 524 / 408;}
.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;}
@@ -127,8 +126,7 @@ a:focus-visible, button:focus-visible {outline: 3px solid #b88719; outline-offse
.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-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: 680 / 2340;}
}
/* Keep the three-card loop readable beside the documentation sidebar. */
@@ -152,3 +150,21 @@ a:focus-visible, button:focus-visible {outline: 3px solid #b88719; outline-offse
[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;}
}
@@ -0,0 +1,6 @@
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</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>