ai-skill-improvelisted

# ai-skill-improve ## Quick start ``` /ai-skill-improve ai-plan # evolve one skill /ai-skill-improve all --dry-run # preview every skill /ai-skill-improve all # batch evolve with evals ``` ## Workflow Improve existing skills using evidence from real project pain (prior eval corpora under `.ai-engineering/evals/`, Engram cross-session observations via `MemoryPort`, `LESSONS.md` operator notes, decision-store, instincts, proposals). The skill owns pain diagnosis and rewrite strategy; it delegates the eval/grade/benchmark pipeline to Anthropic's `skill-creator`. **Output is PR-comment only — never auto-merged** (sub-007 M6). 1. **Phase 0.5** — load corpora (`.ai-engineering/evals/<skill>.jsonl`), Engram observations (`/ai-memory` MCP), and `LESSONS.md` H3 sections that mention the target skill. 2. **Phase 1** — load remaining pain context (decision-store, observations.yml, proposals.md). 3. **Phase 2** — analyze the target skill, score the 5 dimensions. 4. **Phase 3** — generate test prompts that exercise the failing pattern. 5. **Phase 4** — rewrite the skill (Start-Here, pain-injection, scope-gates, structured classification). 6. **Phase 5** — emit the proposed SKILL.md diff as a PR comment via `gh pr comment`. **Do not commit or push.** Operator review is the merge gate. 7. **Phase 6** — verify improvement on the operator's branch (pass-rate delta vs prior iteration). > Detail: see [audit document skeleton](references/output-skeleton.md), [the s