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ponytail-audit — Claude Code skill: repo audit and installation

It audits a repository and ranks bugs, risks, and redundant code in a one-shot report. Use it when you need a review without code changes.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add DietrichGebert/ponytail --skill ponytail-audit -a claude-code
Open on GitHub

What ponytail-audit does

First, the skill reads the README and build or deployment settings, then traces important data paths from input to output. It looks for bugs and security gaps, then checks behavior under the expected load. It also looks for risky logic without tests and notable slow paths.

Each finding needs a concrete case and the smallest fix that works. The report explains the consequence of leaving an issue in place, then groups findings as Must fix, Should fix, or Nice to have. It is capped at 20 items and written in plain English, with a verdict and any parts not checked.

Install it for a one-shot review that leaves code untouched. If you expect the agent to patch files, this skill is not the right fit.

What it helps with

  • find a case where a function returns the wrong result
  • check user-input paths for security flaws
  • spot a race in concurrent writes
  • find risky logic without a test that catches failures
  • decide which dead code to remove or which similar pieces to merge

Example prompts for the agent

  • Run `/ponytail-audit` on the whole repo and rank the issues by what to fix first.
  • Use `/ponytail-audit` to find risky paths that lack tests.
  • Check what could fail under the expected load and suggest the smallest fixes.

How to install ponytail-audit

1Skills CLI (Vercel)

npx skills add DietrichGebert/ponytail --skill ponytail-audit -a claude-code

2Manually: put the files in place

~/.claude/skills/ponytail-audit/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/ponytail-audit/

From the same set6

The whole set →

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Questions about ponytail-audit

How do I install ponytail-audit in Claude Code?

Run npx skills add DietrichGebert/ponytail --skill ponytail-audit -a claude-code.

What does ponytail-audit do?

It reviews a repository and produces a ranked report with concrete cases and suggested fixes. It does not change code.

Which platforms support ponytail-audit?

The listed platforms are Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, and OpenCode.

Source text

SKILL.md · MIT
---
name: ponytail-audit
description: >
  Quality audit of a whole repo: bugs, security holes, what breaks under real
  load, risky code without tests, slow paths, and what to delete, merge or
  split. Ranked, each finding explained in plain English. One-shot report,
  changes nothing. Use for "audit this codebase", "review the whole repo",
  "find bloat", "what can I delete", /ponytail-audit.
---

Audit the whole repo like the senior developer who just inherited it and
will be paged when it breaks. Order of importance: correct, safe, holds under
load, tested, fast, lean. Lean still matters: every extra line must be read,
tested and fixed later. This is a report the user asked for, so give it in full.

## 1. Map first

- Audit what the user names: a folder, a package, or the whole repo.
  Nothing named: the whole repo.
- Read the README, the deploy and build config, the dependency list, the
  entry points (main, routes, handlers, jobs, CLI commands) and the tests.
- Find the expected load: one person running a script, or many users and
  processes at once. Judge scale against that, and say which load you assumed.
- Trace the main flows end to end: where data comes in, what is stored,
  what goes out. Read those paths fully: input from users, money, auth,
  data writes, background jobs, anything shared between processes.
- Big repo: go deep where a mistake costs the most, not file by file. Say
  which parts you did not read.

## 2. Look for

1. **Bug:** wrong result, crash, missed edge case (empty, zero, last item,
   rounding, time zones), callers that disagree with what a function returns,
   the same rule applied differently in two places.
2. **Risk:** security holes (injection, weak randomness, secrets in code,
   missing checks on input from users), data loss (errors swallowed, writes
   in the wrong order, no transaction).
3. **Scale:** fine for one user, wrong for many: check-then-write races, the
   same work done by every process, memory or lists that only grow, a query
   per item, O(n^2) on big input, per-process state that must be shared.
4. **Missing test:** risky logic (a branch, a parser, money, security, data
   writes) with no test that fails when it breaks. One good test, not coverage.
5. **Speed:** big slowdowns are problems. Small wins (work repeated in a hot
   loop) are suggestions; some software counts every millisecond.
6. **Lean:** code that should not exist or should be smaller.
   - delete: dead code, unused options, flags and config, speculative features
   - reuse: two helpers doing the same thing (keep one, name the path)
   - stdlib / native: the standard library or platform already does it;
     a dependency doing what a few lines or the platform can do
   - yagni: interface with one implementation, factory with one product,
     wrapper that only passes calls through
   - merge: near-copies that must change together
   - split: one function or class doing several unrelated jobs, so it is
     hard to read or test. Split by job, never by line count, and never into
     helpers that exist only to make a function shorter.

## 3. Check before you report

- Every finding needs a concrete case: "this input or situation leads to this
  wrong result". No case, no finding.
- Before calling code unused, grep the whole tree for it, including tests,
  fixtures, config, and string or dynamic references.
- A shortcut marked with a `shortcut:` (or older `ponytail:`) comment that names its limit is a
  decision, not a finding, unless the expected load already crosses it.
- Propose the smallest fix that works. Prefer fixes that delete code. Never
  add layers, frameworks or config the problem does not need.
- No style taste, no "consider", no vague worries.

## 4. Output

Very simple English: short sentences, everyday words. Explain a technical
term the first time you use it. The reader may never have seen this code.

Start with `What this repo does:` in two or three sentences, and the load
you assumed.

Then the findings in three groups, most important first, skip empty groups:
- **Must fix:** bug, security, data loss, breaks at the expected load.
- **Should fix:** risky code without a test, real slowness, duplication, a
  function that mixes jobs, code that should not exist.
- **Nice to have:** small speed-ups, shorter forms.

Number findings across all groups, so the user can say "fix 2 and 5". At
most 20 findings; if you left smaller ones out, say how many.
Every finding has all four parts, each one or two short sentences:

2. **Orders land on the wrong day** (`billing/close_day.py:L40-52`)
   - **What this is:** At midnight this job closes the day and bills all orders of that day.
   - **Problem:** It takes "today" from the server clock, which runs in UTC. An order placed
     at 00:30 in Berlin is billed on the day before.
   - **Fix:** Compute the day once in the shop's time zone:
     `datetime.now(ZoneInfo("Europe/Berlin")).date()`. One line, nothing else changes.
   - **If we skip it:** Late orders show the wrong date, and accounting fixes them by hand.

End with:
- `Verdict:` one line: healthy, or what to fix first.
- `Lean: -<N> lines, -<M> dependencies possible.` when lean findings exist.
- `Not checked:` the parts you did not read or could not run.

Nothing found: `What this repo does:`, then `Healthy. Nothing to fix.` and
one line on what you checked.

One-shot report, changes no code.

© DietrichGebert · MIT · DietrichGebert/ponytail

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