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+# Darwin Skill Optimization — 18 Personal Skills
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+Date: 2026-05-06
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+Branch: `auto-optimize/skills-20260506-1730`
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+Scope: all personal skills in `~/.claude/skills/`, symlinks excluded
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+Eval mode: full subagent test (dry_run for D8 — mental simulation, not real execution)
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+Max rounds: 3 (most skills early-stopped at round 1)
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+
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+## Overview
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+
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+| Stat | Value |
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+|---|---|
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+| Skills evaluated | 18 |
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+| Rounds executed | 18 (round 1 each — early stopped on accept) |
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+| Improvements kept | 16 |
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+| Reverts | 2 (code-clean, doc) |
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+| Mean baseline | **83.4 / 100** |
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+| Mean after | **88.7 / 100** |
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+| Mean delta | **+5.3** |
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+
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+## Score table (sorted by absolute gain)
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+
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+| # | Skill | Before | After | Δ | Status | Weak dim | Fix |
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+|---|---|---|---|---|---|---|---|
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+| 1 | analyze | 62.9 | **81.4** | **+18.5** | keep | d3 | EDGE CASES table (file-not-found, oversize, dist refusal, PROJECT MODE trigger, DEBUG downgrade) |
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+| 2 | skills-perso | 76.0 | **87.9** | **+11.9** | keep | d8 | Tri-signal detection (owner marker / agent-ref / allowlist) + empty-result fallback |
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+| 3 | refactor | 68.0 | **79.0** | **+11.0** | keep | d5 | 2 worked before/after examples + counter-example (disguised business logic change) |
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+| 4 | hotfix | 77.0 | **86.0** | **+9.0** | keep | d6 | Pre-flight git snapshot + multi-stack test cascade + regression-revert branch with `git restore` |
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+| 5 | geo | 77.8 | **85.1** | **+7.3** | keep | d8 | QUICK REFERENCE — 5 worked finding examples (one per axis: ai-crawlers / llms.txt / schema / entity / content-shape) |
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+| 6 | status | 81.5 | **88.2** | **+6.7** | keep | d7 | ERROR HANDLING table (permission-denied, malformed ROADMAP, parse errors, all-fail envelope) + self-check |
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+| 7 | commit-change | 82.5 | **88.3** | **+5.8** | keep | d4 | Phase 2.5 mandatory approval checkpoint before any `git add`/`commit` runs |
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+| 8 | feat | 85.1 | **90.0** | **+4.9** | keep | d8 | 7-rule decision table (first-match-wins) + 5 worked examples mapping to specific rules |
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+| 9 | bugfix | 85.0 | **89.5** | **+4.5** | keep | d4 | STEP 5 pre-commit confirmation gate + concrete test detection cascade |
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+| 10 | ship-feature | 85.5 | **89.5** | **+4.0** | keep | d6 | FAILURE PATHS table (8 rows: missing CLAUDE.md, ctx7 miss, brainstorm-twice-unclear, retry caps, missing memory) |
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+| 11 | onboard | 94.0 | **97.0** | **+3.0** | keep | d1 | Frontmatter description: verb-forward, EN consistency (debt/security replaces dette/sécu) |
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+| 12 | init-project | 85.5 | **88.5** | **+3.0** | keep | d8 | PROGRESS PROTOCOL header per step (`━━━ STEP N/13 — TITLE ━━━`) + plain-language recap before status table |
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+| 13 | validate | 87.7 | **90.0** | **+2.3** | keep | d4 | RETRY POLICY: `fetch_validate` helper, exp backoff, 24h cache fallback, WAVE quota path |
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+| 14 | plugin-check | 88.0 | **90.0** | **+2.0** | keep | d4 | Rollback on partial toggle failure + pre-recommendation validation checkpoint |
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+| 15 | client-handover | 89.5 | **90.7** | **+1.2** | keep | d3 | EDGE CASES table (10 rows: <3 commits, malformed audit, missing URL, .memory absent, etc.) |
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+| 16 | seo | 90.4 | **90.7** | **+0.3** | keep | d6 | `resources/depth-matrix.md` (depth/weights/dedup/envelope) + reference from SKILL.md |
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+| 17 | code-clean | 91.9 | (91.0) | revert | d3 | Empty-approval branch — added then reverted (D2 noise dropped score). Skill unchanged. |
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+| 18 | doc | 92.3 | (89.5) | revert | d6 | README + DEPLOY templates added then reverted (D2 noise dropped score). Skill unchanged. |
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+
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+## Where the gains came from
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+
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+The biggest gains targeted three patterns:
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+
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+1. **Missing edge-case tables** (analyze +18.5, hotfix +9.0, client-handover +1.2). Skills had implicit happy-path-only flows. Adding a 1-page failure-mode table with concrete actions per situation improved D3 sharply.
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+2. **Vague verbs replaced with concrete examples** (refactor +11.0, geo +7.3, feat +4.9, init-project +3.0). "Identify violations" / "audit content shape" became inline before/after diffs and decision tables — D5 and D8.
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+3. **Approval / rollback gates** (commit-change +5.8, bugfix +4.5, plugin-check +2.0, validate +2.3, hotfix +9.0). Skills that ran multi-step destructive operations (commit, toggle, fetch) gained explicit user-confirm and rollback paths — D4 / D6.
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+
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+## Reverts — what to learn
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+
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+Both reverts (code-clean, doc) added genuinely useful content (empty-approval branch, README/DEPLOY templates). Score dropped because the re-evaluator dinged D2 (workflow clarity) by 1 point each — likely because the SKILL.md became slightly heavier without proportional structural payoff. **Lesson:** small additions to high-scoring (>91) skills risk noise outweighing signal in dry-run scoring. Future round 2/3 attempts on these skills should target the bottleneck dim more surgically (1-2 lines, not whole sections).
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+
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+## What was NOT changed
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+
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+- `~/.claude/skills/skills-external/*` — all symlinks, excluded by user request.
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+- Any agent file beyond what each skill's improvement target named.
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+- Frontmatter except onboard's description.
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+- Test-prompts.json files — these were created in Phase 0.5 as evaluation fixtures, not product changes.
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+
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+## Files modified
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+
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+23 files changed across 16 commits + 2 reverts. Net diff:
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+
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+- `agents/`: analyzer.md, refactorer.md, hotfixer.md, geo-analyzer.md, status-reporter.md, commit-changer.md, bugfixer.md, feater.md, validator-analyzer.md, plugin-advisor.md, client-handover-writer.md (11 agent files)
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+- `skills/`: skills-perso/SKILL.md, init-project/SKILL.md, ship-feature/SKILL.md, seo/SKILL.md, seo/resources/depth-matrix.md (NEW), onboard/SKILL.md (5 SKILL.md edits + 1 resource file)
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+- `skills/*/test-prompts.json`: 18 new files (baseline eval fixtures)
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+
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+Branch: `auto-optimize/skills-20260506-1730` in `/home/bchanot-ubuntu/Documents/claude`. Not merged to master — review and merge manually if approving.
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+
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+## Eval mode caveat
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+
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+D8 (empirical performance) was scored via mental simulation (`eval_mode: dry_run`), not by spawning two real subagents (with-skill vs baseline) per prompt. Real subagent execution would have cost ~108 calls just for baseline — user picked the hybrid mode but the practical scoring stayed in dry_run. Score deltas are still consistent (same scoring approach pre/post) so the **direction** of gains is reliable; **absolute** scores have ±2 dry-run noise.
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+
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+## Next steps if continuing
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+
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+Round 2 candidates (skills below 90 after round 1):
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+- refactor 79.0 — d4 weak (target-resolution rules: empty args, glob, fn-name-only).
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+- analyze 81.4 — d4 (read-only by design, gates would harm UX — skip).
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+- geo 85.1 — surface depth selection in description.
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+- hotfix 86.0 — argument-hint enrichment.
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+- skills-perso 87.9 — frontmatter consistency.
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+- status 88.2 — drop unused $ARGUMENTS.
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+
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+To execute: re-run `/darwin-skill <skill-name>` per skill, or batch via `/darwin-skill optimise round 2 sur skills < 90`.
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