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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-audit

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

84/100

Supported Platforms

Universal

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.

Substance
26/30
Structure
16/20
Description
15/15
Adoption
12/20
Freshness
15/15

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.

SkillScoreStarsUpdatedFormat
chisle-audit (this skill)by JayPokale84593todaySKILL.md
ai-job-searchby MadsLorentzen10044.9ktodayCLAUDE.md
claude-howtoby luongnv8910041.7k3d agoCLAUDE.md
algorithmic-artby anthropics100177.9k11d agoSKILL.md
pptxby anthropics100177.9k11d agoSKILL.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.

name: 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 → audit HEAD~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.

Related Skills

View on GitHub
GitHub Stars593
CategoryDevelopment
Updated16h ago
Forks39

Languages

JavaScript

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions