ponytail-audit
Performs a complete code audit. It finds bugs, security flaws, slow code, and suggests what to remove or improve.
What it does
This tool analyzes an entire code project to find issues like bugs, security flaws, slowness, and unnecessary code. It presents findings in order of importance, explaining everything simply.
When to use it
- ✓Before releasing a major new feature.
- ✓When an old project needs a thorough review.
- ✓To understand what can be removed or simplified in the code.
Example of what to ask your AI
“Review all this code and tell me the most critical issues.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool reads the project's documentation, configurations, and main code. It simulates how the code would behave with many users and looks for common errors, security vulnerabilities, and inefficiencies.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add DietrichGebert/ponytail --skill ponytail-auditOr download just the file:
curl -L https://raw.githubusercontent.com/DietrichGebert/ponytail/main/skills/ponytail-audit/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
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
- 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.
- 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).
- 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.
- 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.
- Speed: big slowdowns are problems. Small wins (work repeated in a hot loop) are suggestions; some software counts every millisecond.
- 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 olderponytail:) 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:
- 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:
…
FAQ
Does the tool change my code?
No, it only analyzes and generates a report. No changes are made to your project.
What does 'lean' mean?
'Lean' means concise, without excess. The tool looks for code that can be deleted, simplified, or already exists in standard libraries.
How are the issues presented?
Issues are grouped into 'Must fix', 'Should fix', and 'Nice to have'. Each has a clear description, the code location, and a suggested fix.
Details
Original description by the author
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.
repo: DietrichGebert/ponytail
Popularity
- GitHub stars
- 164k
- Ranking position
- #334
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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