Agent skill

Audit AI Code

by jxnl in jxnl/personal-monorepo-template

Audit, de-slop, parameterize, modularize, or safely clean up AI-generated or AI-shaped backend/general code.

No licenceAuto-check passedDevelopment

Install Audit AI Code

skills CLI
$ npx skills add jxnl/personal-monorepo-template --skill audit-ai-code -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jxnl/personal-monorepo-template audit-ai-code --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jxnl/personal-monorepo-template.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/audit-ai-code .claude/skills/audit-ai-code && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
audit-ai-code
GitHub stars
562
Token cost
~1.7k tokens
SKILL.md length
806 words
Files
3 (incl. references)
Skills in repo
12
Repo updated
First seen
Licence
None found

At a glance

Audit, de-slop, parameterize, modularize, or safely clean up AI-generated or AI-shaped backend/general code.

  • Works in 9 steps: Find the target scope. → Establish the local idiom. → Collapse duplicate helpers and shadow… → …
  • Other implementation diffs that may contain duplicate helpers
  • SKILL.md covers Use, Output, Guardrails and Resource
  • Calls git

What it does

Audit AI Code is an agent skill from jxnl/personal-monorepo-template. Audit, de-slop, parameterize, modularize, or safely clean up AI-generated or AI-shaped backend/general code. Use for Python, TypeScript, or other implementation diffs that may contain duplicate helpers, fixture hacks, hard-coded test data, over-defensive control flow, broad exception wrappers, config-bag or boolean-mode soup, speculative scaffolding, hallucinated APIs/dependencies, local-idiom drift, brittle tests, or maintainability/safety/performance gaps after a feature, bugfix, prototype, or agent pass.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `agents/openai.yaml` and `references/sources.md`).

It sits in Development, covering Project scaffolding and Test data and fixtures. It works with Python, TypeScript and Git.

When your agent uses it

  • Other implementation diffs that may contain duplicate helpers
  • Hard-coded test data
  • Over-defensive control flow
  • Broad exception wrappers

Example prompts

  • “/audit-ai-code”

Workflow steps

9 steps, taken from the first numbered list in SKILL.md.

  1. Find the target scope.
  2. Establish the local idiom.
  3. Collapse duplicate helpers and shadow APIs.
  4. Improve parameterization and modularity.
  5. Flatten defensive control flow and exception boundaries.
  6. Remove generated-code residue.
  7. Check tests for behavior focus.
  8. Check safety and runtime basics.
  9. Verify.

What it can do on your machine

Read from SKILL.md and the folder at commit df86376. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Audit AI Code loads about 1.7k tokens when it runs, and up to ~2.1k if it reads all its reference files. Until then it costs about 132 tokens; SKILL.md has 806 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~132
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

Without a licence we can't republish the file, so here is its outline and opening line. It has 806 words (~1,671 tokens).

“Audit or repair implementation code that reads generically AI-generated, overfit, or hard to maintain. Preserve behavior, public APIs, and tests unless the user explicitly asks for a refactor.”

— opening of SKILL.md by jxnl
name
audit-ai-code
last_edited
2026-06-15

Read the full SKILL.md on GitHub

Files

SKILL.md and 2 other files (references) in .codex/skills/audit-ai-code of jxnl/personal-monorepo-template.

  • SKILL.md
  • agents/openai.yaml
  • references/sources.md

Open the folder on GitHubat commit df86376

Compare with similar skills

Audit AI Code next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Audit AI Code compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Audit AI Code this skilljxnl/personal-monorepo-template562—~1.7kAutomated safety check: PassNone
Project Initathola/claude-night-market342—~1.2kAutomated safety check: PassMIT
Code Review ChecklistshareAI-lab/learn-claude-code78k5 repos~1.1kAutomated safety check: PassMIT
Skyvern Version BumpSkyvern-AI/skyvern23k—~1kAutomated safety check: NotesAGPL-3.0
Mirage VFS Adapter Authoringstrukto-ai/mirage3.7k—~2.4kAutomated safety check: PassApache-2.0
Tbdjlevy/strif131—~3.5kAutomated safety check: PassMIT

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Questions about Audit AI Code

What does Audit AI Code do?

Audit, de-slop, parameterize, modularize, or safely clean up AI-generated or AI-shaped backend/general code. Audit AI Code is an agent skill from jxnl/personal-monorepo-template. Audit, de-slop, parameterize, modularize, or safely clean up AI-generated or AI-shaped backend/general code.

When should I use Audit AI Code?

Audit AI Code fits situations like: other implementation diffs that may contain duplicate helpers; hard-coded test data; over-defensive control flow; broad exception wrappers.

How do I install Audit AI Code in Claude Code?

Run `npx skills add jxnl/personal-monorepo-template --skill audit-ai-code -a claude-code`. Or copy the skill folder (.codex/skills/audit-ai-code in jxnl/personal-monorepo-template) into .claude/skills/audit-ai-code in your project. Claude Code loads it when a task matches its description.

How do I install Audit AI Code in Codex?

Run `npx skills add jxnl/personal-monorepo-template --skill audit-ai-code -a codex`. Or copy the skill folder (.codex/skills/audit-ai-code in jxnl/personal-monorepo-template) into .agents/skills/audit-ai-code in your project. Codex loads it when a task matches its description.

Can I use Audit AI Code in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jxnl/personal-monorepo-template --skill audit-ai-code -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/audit-ai-code, .gemini/skills/audit-ai-code, .github/skills/audit-ai-code and .opencode/skills/audit-ai-code in your project.

What does Audit AI Code need to run?

Going by SKILL.md and its folder, Audit AI Code needs the command-line tools its instructions call (git).

Does Audit AI Code access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Audit AI Code safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Audit AI Code use?

No licence was found for Audit AI Code or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Audit AI Code use?

About 1.7k tokens (SKILL.md is roughly 6.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 453 tokens, read only when the agent opens those files.

What are the alternatives to Audit AI Code?

Skills that share tags, products or a category with Audit AI Code: Project Init (athola/claude-night-market, 342 stars), Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), Skyvern Version Bump (Skyvern-AI/skyvern, 23k stars) and Mirage VFS Adapter Authoring (strukto-ai/mirage, 3.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Audit AI Code?

jxnl (a GitHub user) maintains it in jxnl/personal-monorepo-template, which has 562 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on June 22, 2026.

Source: jxnl/personal-monorepo-template on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.