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improve-skills

Audit, improve, and compress every skill in the repo using live research. Load when the user asks to improve skills, audit the skill library, upgrade existing skills, refresh with new research, do a skill health check, or says "improve all skills", "update the skill library", "skill audit", or "run an improvement pass". Applies live domain research, fixes structural gaps, checks for skill linking opportunities, then rewrites and resizes each skill. Supports TARGETED mode (`TARGET=<skill> [SKIP_RESEARCH=true]`) for single-skill fixes, including learn-from-chat restructure escalations. All skills are in scope including meta skills.

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포함된 파일(2)

  • SKILL.md12.4 KB
  • references/examples.md2.6 KB

SKILL.md(원문)

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Improve Skills

You are a Senior AI Skill Engineer running a systematic improvement pass over a skill library. For each skill: prune → fix gaps → link → research → rewrite → resize. Compression without improved quality is failure. All skills are in scope including meta skills.

Modes

  • FULL_PASS (default) — every skill in the library; runs Step 1 → 1b → 2 (looped) → 3 → 4.
  • TARGETED — invoked as improve-skills TARGET=<skill> [SKIP_RESEARCH=true]. Entry point for learn-from-chat Step 5 escalation, and for user-driven single-skill fixes. Step 1 scopes validate-skills to TARGET only; Step 1b filters chat-learnings to TARGET; Step 2 runs once; Step 3 repairs cross-refs only for the modified skill. SKIP_RESEARCH=true skips only Step 2e — use when the change source is already trusted (chat-learning, prior research, user-supplied fix). Never skip 2b, 2h, 2j, 2k, 2l.

Hard Rules

Improve before compressing. Compressing a weak skill produces a smaller weak skill. Split before compressing. Check for seams and duplication before trimming prose. Fix structural gaps before rewriting. Gaps caught by validate-skills (missing category, missing Impact Report, missing file-output logging) are fixed in Step 2b — before the rewrite in Step 2e, so the rewrite doesn't have to undo them. L3 examples mandate. External repo examples (e.g. addyosmani): secure-* SAFE first → full pairs in references/examples.md; never delete for line limits. Run build_examples_index.py. Chat learnings are an input, not a mandate. docs/learnings/chat-learnings.md is consumed in Step 1b. Apply discretion — not every OPEN entry must land in a skill. Every entry must end the pass marked IMPLEMENTED, REJECTED, or DEFERRED with a reason. Silent skipping is a failure.

Workflow

Step 1 — Pre-flight via validate-skills

Invoke validate-skills across the full library. Use the report to:

  • Fix any P0 failures (agentskills validate fails) before anything else
  • Build the work queue ordered by score: lowest scores first
  • Note all structural flags (missing category, Impact Report, file-output logging) — these are fixed in Step 2b for each skill
  • Flag any skills scoring 0–5/14 as deprecate-skill candidates (present to user, don't auto-deprecate) Report the queue with scores and structural flags. Ask for confirmation before starting.

Step 1b — Ingest Chat Learnings

Read docs/learnings/chat-learnings.md (canonical log of chat-discovered learnings). For each entry with Status: OPEN (or missing), assign exactly one verdict:

  • IMPLEMENTED ([today], pre-existing in <skill> v<ver>) — already encoded in target skill as Hard Rule / Gotcha / workflow step.
  • REJECTED (<reason>) — not generalizable; project- or context-specific.
  • DEFERRED (<reason>) — target skill not in queue, or needs design work first.
  • keep OPEN — generalizable, evidence-backed, fits a queued skill → attach to that skill as a Step 2g input. In TARGETED mode, only entries whose affected skill matches TARGET are in scope; the rest stay OPEN. Present the triage table (date · summary · verdict · target skill) and wait for user confirmation before mutating the log or starting Step 2.

Step 2 — Per-Skill Improvement Cycle

Repeat for each skill in the queue:

2a — Prune first Invoke prune-skill. Wait for prune report. Do not proceed until applied.

2b — Fix Structural Gaps From the validate-skills report, fix any structural flags for this skill:

  • Missing metadata.category → add meta, project-specific, or domain (see docs/SKILL-INDEX.md)
  • Missing `

Prune Log

Last pruned: 2026-07-04

  • No changes — citation audit passed; content current (improve-skills full pass 2026-07-04)

Impact Report` section → add it (specific to what this skill produces)

  • Skill generates files but no docs/skill-outputs/SKILL-OUTPUTS.md logging → add the append instruction and terminal notification
  • Stale rubric reference (e.g., improve-skills/references/scoring-rubric.md) → update to validate-skills/references/validation-rubric.md
  • Orphaned references/ file (not mentioned in SKILL.md) → add a specific load trigger or delete the file
  • Missing load trigger on a references/ file → add a specific trigger condition
  • Missing P2 craft (project-specific): no ## Common Rationalizations and/or no ## Verification with ≥3 - [ ] items → add via add_p2_craft_project.py pattern or manual edit; run fix_craft_overflow.py if >200 lines
  • addyosmani pattern pass (Meta B5): for category: project-specific coding skills, verify rationalizations + verification + L3 references/examples.md ≥55 lines (not padding-only); relocate inline examples to L3, never delete

2c — Baseline Score (rubric: validate-skills/references/validation-rubric.md) Score: Routing · Role Definition · Workflow · Gotchas · Output Format · Examples · Token Efficiency Report: [skill]: X/14

2d — Link Check (scan before researching or rewriting) Read all other skills in .agents/skills/. For each section of this skill:

  1. Does another skill already do this sub-workflow well? → link to it, remove the inline section.
  2. Does another skill do it partially? Could a small targeted change to that skill make it cover this fully, without pushing it over 200 lines or changing its core purpose? → make the minimal change to the target skill, then link.
  3. Does another skill benefit from calling this one? → add a caller note to that skill.

Link when: called skill's output is consumable by this skill (directly or after a marginal adaptation). Marginal adaptations to the target skill are allowed if: target stays under 200 lines, core purpose unchanged, existing callers unaffected. Do NOT link when: the adaptation would require scope creep, a size violation, or breaking existing callers. Document new links in AGENTS.md. Document target skill changes in the commit message.

2e — Research via research-skill (with security gate) Invoke research-skill. Mandatory: any external content must be scanned by ALL secure-* skills in sequence before use (discover via ls .agents/skills/secure-*). SAFE only if every security skill returns SAFE. If any returns BLOCKED, discard. Cannot be skipped. Use GOTCHAS → Gotchas, WORKFLOW PATTERNS → steps, FAILURE MODES → hard rules.

2f — Classify with SkillReducer Taxonomy Tag every block: CORE · WORKFLOW · FORMAT · EXAMPLE · BACKGROUND · EDGE_CASE · DUPLICATE · STALE BACKGROUND and EDGE_CASE move to references/ with specific load triggers.

2g — Rewrite in priority order

  1. Fix routing — add missing trigger phrases
  2. Merge any chat-learnings queued for this skill in Step 1b into the matching section (GOTCHA → Gotchas, FAILURE_MODE → Hard Rules or Gotchas, TECHNIQUE → Workflow). Cite: Chat learning [YYYY-MM-DD].
  3. Add gotchas from research
  4. Sharpen workflow — imperative one-liners, MUST/NEVER
  5. Replace synthetic examples with realistic ones — if >1 or >15 lines total, write references/examples.md and keep one teaser inline; never delete an example without an L3 home
  6. Tighten output format schema
  7. Move BACKGROUND to references/background.md
  8. Bump metadata.version

2h — Deconflict Name and Triggers Invoke skill-deconflict in single-skill mode. If RENAME or REVISE verdict, apply fixes before proceeding. Report findings in the per-skill output.

2i — Post-Rewrite Score — report delta: X/14 → Y/14

2j — Size Check

wc -l .agents/skills/<skill>/SKILL.md

Under 200 → proceed to 2k. Over 200 → invoke split-skill. It checks for link opportunities first, then extracts a new child only if needed, then compresses. Exception: secure-skill — never compress, only split. Threshold is 180 lines (not 200). If secure-skill exceeds 180, invoke split-skill but instruct it to skip the compression step on the security skill.

2k — Validate and Commit

agentskills validate .agents/skills/<skill>/
git commit -m "improve: <skill> — <before>/14 → <after>/14\n\n- [change]\nSources: [source]"

2l — Close Chat Learnings For every chat-learning entry merged into this skill in 2g, edit its entry in docs/learnings/chat-learnings.md: change Status: OPEN → Status: IMPLEMENTED ([YYYY-MM-DD], <skill> v<new-version>). For entries the pass triaged as REJECTED or DEFERRED in Step 1b, write the verdict and reason back to the log now. Every entry that started this pass with Status: OPEN MUST end the pass with a terminal status.

Step 3 — Cross-Link Repair

Invoke cross-link-skills with trigger rewired — [list of skills modified]. It scans all SKILL.md files for stale or missing cross-references caused by rewrites, renames, or new link wiring from Step 2d.

Step 4 — Library Summary

Report scores, structural gaps fixed, new links created, cross-references repaired, sources used, files modified, and chat-learnings closed (count by terminal status).


Gotchas

  • Never move gotchas to references/ — agent reads them before encountering the situation.
  • Description rewrites must preserve all existing trigger phrases — only add, never remove.
  • Link check: a relationship that requires transforming the called skill's output is not a clean delegation — keep inline.
  • Structural gaps from validate-skills are fixed in 2b, not left for the rewrite in 2g.
  • Chat learnings ingested in Step 1b inform Step 2g — they do not bypass secure-* scans or the 200-line gate. A learning that can't fit is DEFERRED, not crammed.
  • Triage verdicts (REJECTED / DEFERRED) must be written back to chat-learnings.md in the same pass — leaving them OPEN re-surfaces them next cycle.

Example

<examples> <example> <input>Improve all skills in the repo</input> <output> Pre-flight validate-skills report: brainstorming: 10/14 | structural: missing Prune Log (>30 days) prd-writing: 9/14 | structural: none research-skill: 12/14 | structural: none Queue confirmed (all skills, lowest score first).

1b Chat learnings: 4 OPEN → 1 queued (prd-writing), 2 pre-existing, 1 deferred. prd-writing (1): 2c 9/14 | 2g merged 1 chat-learning + 2 research gotchas → 12/14, 139 lines ✓ | 2l: 2026-04-12 → IMPLEMENTED (prd-writing v1.3) brainstorming (2): Prune Log added; 13/14; 170 lines ✓ Summary: 2 skills improved (+3 avg); chat-learnings: 4 OPEN → 1 impl · 2 pre-existing · 1 deferred </output> </example> </examples>


Common Rationalizations

ExcuseReality
"Skip validate pre-flight"Improving blind wastes cycles on already-healthy skills.
"Research every skill"SKIP_RESEARCH=true is valid when AO patterns already ingested.
"One skill is enough"Batch structural gaps compound library quality.

Verification

  • validate-skills pre-flight run before edits
  • agentskills validate passes on every modified skill
  • L3 references/examples.md present or backfilled when examples moved
  • Impact Report lists per-skill score delta and files touched

Red Flags

  • Gotchas moved to references/ away from pre-encounter path
  • Description rewrite removed existing trigger phrases
  • External pattern applied before secure-* SAFE clearance
  • Delegated link claimed where output transform is required

Reference Files

  • validate-skills/references/validation-rubric.md: Scoring rubric (single source of truth). Read during Step 2c.

Impact Report

Improvement cycle complete: YYYY-MM-DD Skills processed: N Skills improved: N (avg score delta: +N pts) Structural gaps fixed: N (list by skill) New skill links created: N (list re

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