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Magnus HedemarkGitHubusername <username>factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>* feat(product-lifecycle-learning): add product lifecycle learning skill (#194) Introduce a new skill to close the launch-to-learning loop for product features and capabilities. Covers: - Post-launch outcome review with explicit epistemic categories (expected/observed/uncertain/inferred) - Assumption ledger updates with confidence shifts - Multi-dimensional feature health assessment - Six lifecycle decisions: continue/improve/harvest/pivot/pause/retire - Full retirement lifecycle: deprecation communication, migration paths, customer treatment during sunset, and internal cleanup - Durable retained learning records that feed back into roadmap, analytics, adoption, experimentation, and specifications Ships 4 references (discovery brief, epistemic discipline, retirement lifecycle, feedback destinations), 6 templates (outcome review, assumption ledger update, feature health record, retirement decision, sunset plan, retained learning record), and 7 eval cases including adversarial coverage. Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com> * fix(product-lifecycle-learning): regenerate marketplace with corrected description The Claude marketplace JSON contained the original description starting with "Close" which was replaced with "Compare" to satisfy the imperative-verb quality check. Regenerate to match the corrected SKILL.md frontmatter. Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com> * fix(product-lifecycle-learning): regenerate llms.txt with corrected description Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com> --------- Co-authored-by: username <username> Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
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Feature Health Record
Assess feature health across multiple dimensions. Do not reduce to a single score or traffic-light color. Each dimension has its own evidence, confidence, and trend.
Feature Identity
| Field | Value |
|---|---|
| Feature / capability name | |
| Assessment date | |
| Assessor | |
| Prior health record date |
Health Dimensions
1. Adoption Health
| Metric | Value | Confidence | Trend (over 3 cycles) | Threshold for concern |
|---|---|---|---|---|
| Activation rate | Improving / Stable / Declining | |||
| Time-to-value (median) | ||||
| Feature discovery rate | ||||
| Sustained use (DAU/WAU/MAU as appropriate) | ||||
| Cohort retention (30/60/90-day) |
Adoption health summary: (narrative, with evidence)
2. Technical Health
| Metric | Value | Confidence | Trend | Threshold for concern |
|---|---|---|---|---|
| Error rate | ||||
| P95/P99 latency | ||||
| Availability (uptime %) | ||||
| Known bugs (open, by severity) | ||||
| Dependency freshness (outdated deps) |
Technical health summary: (narrative, with evidence)
3. Operational Health
| Metric | Value | Confidence | Trend | Threshold for concern |
|---|---|---|---|---|
| Support ticket volume | ||||
| Time-to-resolution (median) | ||||
| Alert frequency (false positives, actionable) | ||||
| On-call burden (pages per week) | ||||
| Documentation freshness |
Operational health summary: (narrative, with evidence)
4. Strategic Health
| Factor | Assessment | Evidence |
|---|---|---|
| Alignment with current strategy | Strong / Moderate / Weak | |
| User need confirmed | Yes / Partial / No | |
| Competitive differentiation | Strong / Moderate / Weak / None | |
| Revenue or value contribution | ||
| Replacement or alternative exists | Yes / Partial / No |
Strategic health summary: (narrative, with evidence)
Cross-Dimension Patterns
Are there correlations or conflicts across dimensions? (e.g., "High adoption but declining technical health — investment in reliability needed" or "Strong strategic alignment but no adoption — discovery or positioning problem")
Overall Assessment
- Strongest dimension:
- Weakest dimension:
- Most concerning trend:
- Most improved since last assessment:
- Recommended lifecycle decision direction: (continue / improve / harvest / pivot / pause / retire — preliminary, to be confirmed by the formal decision record)