chisle-audit
One-shot efficiency audit of a file, diff, or whole repo across BOTH axes at once: over-engineered code (reinvented stdlib, needless abstractions, speculative config) AND bloated prose (verbose comments, padded docstrings, redundant doc sections).
Install / Use
npx skills add JayPokale/Chisle --skill chisle-auditInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Our assessment of chisle-audit
chisle-audit scores 84/100 on our quality scale, 2510th of 4,634 Development & Engineering skills we index.
Its SKILL.md is 2.7 KB long, split into 5 sections with 2 code examples: a solid amount of guidance for an agent.
It has 593 GitHub stars, a meaningful sign that others use it.
Maintenance, license and trust
- The repository was last updated today, so chisle-audit is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
chisle-audit compared with similar skills
All 4 of these similar skills score higher than chisle-audit; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| chisle-audit (this skill)by JayPokale | 84 | 593 | today | SKILL.md |
| ai-job-searchby MadsLorentzen | 100 | 44.9k | today | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 41.7k | 3d ago | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 11d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 11d ago | SKILL.md |
Frequently asked questions
- How do I install chisle-audit?
- Run
npx skills add JayPokale/Chisle --skill chisle-audit. The install tabs above show the steps for each supported agent. - Which AI agents does chisle-audit work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is chisle-audit safe to use?
- It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is chisle-audit still maintained?
- The repository was last updated today, so chisle-audit is actively maintained.
Skill content
View source on GitHubname: chisle-audit description: > One-shot efficiency audit of a file, diff, or whole repo across BOTH axes at once: over-engineered code (reinvented stdlib, needless abstractions, speculative config) AND bloated prose (verbose comments, padded docstrings, redundant doc sections). Neither a pure code-minimizer nor a pure prose compressor does both in one pass. That's the point. Ranked report, biggest saving first; changes nothing. Use when the user says "chisle audit", "/chisle-audit", "audit this for bloat", "what can I cut", "review this PR for over-engineering and verbosity".
Chisle Audit
Scan the target (a diff, a file, or the repo tree) and report what to cut, on both axes. One-shot. Read-only: never edit, never write a flag, never apply fixes.
Scope
- No argument → audit the current
git diff(staged + unstaged). Empty diff → auditHEAD~1..HEAD. - A path → audit that file or directory.
- "repo" / "whole repo" → walk the tree (skip vendored/generated/
node_modules/dist/lockfiles).
What to flag
Code (the YAGNI axis):
- Reinvented stdlib (hand-rolled debounce, deep-clone, groupBy, retry loop, date math)
- Abstraction with one implementation (interface/factory/wrapper for a single case)
- New dependency for what a few lines or an installed dep already covers
- Config/option/flag that never varies
- Speculative "for later" scaffolding with no current caller
- Verbose code where a native platform feature (CSS, DB constraint,
<input type>) does it
Prose (the compression axis), the half a code-only auditor misses:
- Comments that restate the code (
i += 1 // increment i) - Docstrings/READMEs padded with filler, hedging, ceremony, or duplicated content
- Multi-paragraph explanations where one tight sentence carries the meaning
- Decorative tables/emoji/headings that add tokens, not information
- Dead prose: TODO graveyards, stale "see also" links, obsolete sections
What NOT to flag
Input validation at trust boundaries, error handling that prevents data loss,
security, accessibility, deliberate // chisle: / // ponytail: shortcuts already
documented, or domain comments that explain why (not what).
Output
One ranked list, biggest cut first. One finding per line. No preamble, no praise.
path:line [code|prose] <what's bloated> → <the lean replacement>. (~N lines/tokens)
End with a two-line summary:
N findings: X code, Y prose. Est. removable: ~A lines code, ~B lines prose.
Biggest win: <the single highest-impact cut>.
Be honest about uncertainty: mark a finding (check) if cutting it might lose
behavior you can't verify from the snippet. Lean toward fewer, high-confidence
findings over a long speculative list.
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
