* 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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Retirement / Continuation Decision
Make and record a lifecycle decision: continue, improve, harvest, pivot, pause, or retire. This decision requires human judgment informed by evidence. No automated threshold or formula replaces context and accountability.
Feature Identity
| Field | Value |
|---|---|
| Feature / capability name | |
| Decision date | |
| Decision-maker (name and role) | |
| Prior decision (if any) and date |
Evidence Considered
| Source | Date | Key findings |
|---|---|---|
| Outcome review | ||
| Assumption ledger | ||
| Feature health record | ||
| Other (specify) |
Decision
Decision: (Continue / Improve / Harvest / Pivot / Pause / Retire)
Rationale: (Why this decision, not the other five? Cite the specific evidence that drove the choice. If retiring, explain why harvest or pivot was rejected. If continuing, explain why improve or harvest was not selected.)
Context considered:
- Product and market context:
- User base and impact:
- Available alternatives for users:
- Business priorities and resource constraints:
- Strategic alignment:
Risks of this decision:
- If we are wrong, what breaks?
- What would change our mind?
Risks of NOT making this decision (status quo):
- What deteriorates if we defer?
Accountable Human Judgment
Decision-maker: (name and role — must be a human, not an automated system or threshold)
I confirm that I have reviewed the evidence above and made this decision based on my judgment of the product, market, user, and business context.
Sign-off date:
If Retire: Sunset Triggers
| Trigger | Date / condition |
|---|---|
| Deprecation announcement | |
| End-of-life (last day of full support) | |
| End-of-support (last day of limited support) | |
| Removal (feature removed from product) | |
| Internal cleanup complete | |
| Learning closure recorded |
Sunset plan: (link to sunset-plan.md or fill here)
If Not Retire: Follow-Up
| Action | Owner | Due date |
|---|---|---|
| Next review date | ||
| Metrics to monitor | ||
| Triggers that would change the decision |
Routing
- Decision routed to roadmap (product-roadmapping-and-portfolio)
- If retire: sunset plan routed to customer-success (conditional-customer-success)
- Learning routed to retained learning record