skill-auto-improver
Improve an external, legacy, or drifted SKILL.md to the skill-creator standard — hard validation gates plus an advisory predictability audit. Don't use for authoring from scratch (skill-creator output is already standard), bulk eval, or prose edits.
npx skills add luongnv89/asm --skill skill-auto-improver --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Skill Auto-Improver You run an eval-driven loop that **retrofits an existing SKILL.md to the current skill-creator standard**. This is the remediation tool for skills that did **not** go through skill-creator — external, legacy, manually-authored, or drifted. Fresh skill-creator output is publish-ready by construction (see skill-creator's `predictability-rubric.md` → _Publish-ready — no auto-improver dependency_) and should **not** normally need this skill. The target must clear **two hard gates**, then gets one **advisory** audit: 1. **Gate 1 — skill-creator standard (must-pass floor)** — `quick_validate` clean, Frontmatter Audit passes, ≤500 lines (detail below). 2. **Gate 2 — asm-eval floor (supplementary)** — `overallScore > 85` AND every category `>= 8`. 3. **Advisory — predictability audit (Phase 2b, not a gate)** — judgment-based findings against skill-creator's rubric, reported separately, **never** blocking. A skill that scores 92 but fails `quick_validate.py` is not done; one that passes `quick_validate.py` but scores 70 is not done. **Both gates must clear, or the loop reports a blocker** — open predictability findings alone never make one. ## Repo Sync Before Edits (m
- Repo Sync Before Edits (mandatory)
- When to Use
- Prerequisites
- Inputs
- The Gates
- Gate 1 — Skill-creator standard (must-pass floor)
- Gate 2 — asm-eval 85/8 quality floor (supplementary)
- Advisory — predictability audit (not a gate)
- Workflow
- Phase 0 — Capture baseline against both gates
- Phase 1 — Apply deterministic fixes, then normalize frontmatter
- Phase 2 — Fix Gate 1 failures first
- Phase 2b — Audit against the predictability rubric (advisory)
- Phase 3 — Fix the lowest asm-eval categories
git fetch origin
git pull --rebase origin "$branch"
test -f "$QV" || { echo "skill-creator not installed at $QV"; exit 1; }
test -f "$RUBRIC" || echo "⚠ predictability rubric missing — Phase 2b degraded (gates unaffected)"
mkdir -p .asm-improver
asm eval "$SKILL_PATH" --json > .asm-improver/baseline.json
python "$QV" "$SKILL_PATH" > .asm-improver/baseline-quickvalidate.txt 2>&1 || true
asm eval "$SKILL_PATH" --fix --dry-run # preview the diff
asm eval "$SKILL_PATH" --fix # write, creates SKILL.md.bak
asm eval "$SKILL_PATH" --json > .asm-improver/iter-1.jsonWhat does the skill-auto-improver skill do?
Improve an external, legacy, or drifted SKILL.md to the skill-creator standard — hard validation gates plus an advisory predictability audit. Don't use for authoring from scratch (skill-creator output is already standard), bulk eval, or prose edits.
How do I install it?
Run `npx skills add luongnv89/asm --skill skill-auto-improver --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From luongnv89/asm, a repository with 782 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.
