Skills dietrichgebert ponytail Ponytail

ponytail-audit

Use it when:
You've inherited a codebase, or want to know what in yours to fix or delete first.
It does:
Maps the repo first, from README, deploy config and dependencies to entry points and tests, then traces the main data flows end to end.
You get:
Up to 20 ranked findings in plain English, each with the problem, the fix and the cost of skipping it, and a verdict on what to fix first.
Also reports:
How many lines and dependencies could go, and which parts it didn't read or couldn't run.
Unlike ponytail-review:
That one checks one change and the code it touches.
Won't:
Change any code; it's a one-shot report.

Skill 3 of 5 in the Ponytail bundle, after ponytail-review and before ponytail-debt.

TL;DR

Ponytail is a skill set that makes coding agents write the least code that fully solves a task; this skill audits a whole repo, or a folder or package you name, like the senior developer who just inherited it. It reads the README, build and deploy config, dependency list, entry points and tests, works out the expected load and says what it assumed, and traces how data comes in, is stored and goes out, reading the riskiest paths in full: user input, money, auth, data writes, background jobs and anything shared between processes. On a big repo it goes deep where a mistake costs most and names the parts it skipped. Findings rank by correct, safe, holds under load, tested, fast and lean, and lean findings name what to delete, reuse, merge or split, such as an interface with one implementation or a dependency doing what a few lines could. Before calling code unused, it greps the whole tree, including tests, config and dynamic references. Every finding needs a concrete case that goes wrong, and they come grouped as Must fix, Should fix and Nice to have, numbered so you can pick which to fix.

Summarizes the skill at 96608e0.

npx skills add https://github.com/dietrichgebert/ponytail --skill ponytail-audit
Weekly Downloads week to Nov 9, 2026
4,302
+82% in 8 weeks

More weekly downloads than 88% of skills

Weekly values
Week toInstalls
Sep 212,370
Sep 282,293
Oct 53,020
Oct 124,843
Oct 195,407
Oct 265,602
Nov 25,460
Nov 94,302
Total Downloads on skills.sh
55,000

More downloads than 82% of skills

Repo stars dietrichgebert/ponytail
187,013

More stars than 95% of repos

Age published Jun 14, 2026
4 months

Newer than 82% of skills

Category

Find root causes, review code and test what you built.

Everything for building software: planning, coding, debugging, design, frameworks, cloud, agents and skills.

Type

A multi-step process the agent follows: interview, debug, run a TDD loop, review.

Effect

Adds no side effects of its own. It shapes how the agent thinks, writes or reviews. Guidelines and routers are always effect:none, even when the task they support edits code.

Needs

Instructions only. Works in any agent that supports skills.

Publisher

Everyone else. Unverified vendor claims default to community.

Topics

SKILL.md

From dietrichgebert/ponytail at 96608e0. Checked daily, last changed Nov 6, 2026.

Frontmatter
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:

  1. 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.