Conciseness

The core templates are operational and lean, but there is more than minor over-explanation: the context-maintenance contract is pointed to three separate times ("Use [references/context-maintenance.md]... keep unknowns explicit", "see `references/context-maintenance.md`", "Update the existing contract using `references/context-maintenance.md`"), the Detection Triggers section largely re-enumerates triggers already in the description, and the Best Practices / Multi-Agent Support / Copilot Chat sections restate generic advice. This fits 'Mostly efficient but includes some unnecessary explanation or could be tightened' better than the 4 anchor's 'minor instances'.

Actionability

Guidance is copy-paste ready throughout: complete markdown entry templates with every field, executable grep commands ("grep -n "Pattern-Key: <pattern_key>" .learnings/LEARNINGS.md"), an exact ID format with examples ("LRN-20250115-001"), and a concrete extraction script invocation including a "--dry-run" first pass. This matches 'Fully executable; copy-paste ready code or commands; specific examples cover the common cases'.

Workflow Clarity

Multi-step processes are clearly sequenced with explicit checkpoints: the extraction workflow runs a dry-run, then "Verify: Read skill in fresh session to ensure it's self-contained"; the ingestion workflow mandates search-before-create dedupe against a stable Pattern-Key; and skill edits are gated by both the Quality Gates checklist and "explicit scoped approval". This matches 'Clear sequence with explicit validation steps; feedback loops for error recovery; checklists for complex processes' rather than the 4 anchor's 'minor validation gaps'.

Progressive Disclosure

Structure is good: setup and hooks are correctly deferred to clearly signaled references with explicit read conditions ("Read these only when installing or configuring the skill"), and all four referenced files exist and are one level deep. However, references/examples.md (383 lines of entry examples) is never linked from SKILL.md, making an entire bundle file undiscoverable — a real organization gap that keeps this at 'minor organization gaps' (4) rather than 5, though references are too clearly signaled to drop to the 3 anchor.

Specificity

The description names multiple concrete actions on named artifacts: "Captures learnings, errors, corrections, and feature requests", "distill into a memory file or new skill", and "review learnings before major tasks". This matches the anchor 'Lists multiple specific concrete actions; comprehensive coverage' rather than the 4 anchor, which reserves room for coverage gaps — the what/when/how-promoted span of this skill is covered without omission.

Completeness

Both questions are explicitly answered: the what ("Captures learnings, errors, corrections, and feature requests to enable continuous improvement") and the when via a five-item "Use when:" enumeration with concrete trigger phrases. It matches the anchor 'Clearly and explicitly answers both what AND when with concrete trigger phrases'; a missing/weak 'when' clause would cap it at 3, which clearly does not apply.

Trigger Term Quality

Trigger language includes directly quoted user utterances — "'No, that's wrong...'", "'Actually...'" — plus natural trigger conditions like "User requests a capability that doesn't exist" and "knowledge is outdated or incorrect". This is the most natural phrasing a user would actually say, matching the comprehensive-synonyms anchor rather than the 4 anchor ('a few natural terms missing').

Distinctiveness Conflict Risk

It has a clear niche (passive accumulation and promotion of learnings) and explicitly redirects the two adjacent skills: "For ACTIVE runtime failures... use `self-healing` instead" and "For CI-only/headless learning capture, use self-improvement-ci". This is more than the 4 anchor's 'minor overlap risk' — the main collision candidates are disambiguated inline, leaving minimal conflict risk.