# Ponytail Audit

> audit, over-engineering, yagni, deletion, simplification

- Skill: `lost-rob0t/ponytail-audit` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add lost-rob0t/ponytail-audit`
- Raw SKILL.md: https://api.skillmd.com/api/skills/lost-rob0t/ponytail-audit/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Security
- License: MIT
- Author: lost-rob0t (https://skillmd.com/u/lost-rob0t)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/lost-rob0t/ponytail-audit

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# Ponytail Audit

> External import of **Ponytail** by Dietrich Gebert and contributors, adapted from upstream v4.9.0 under MIT.

## Goal

Run the Ponytail over-engineering review across an entire repository.

## Input

A repository tree and enough source/dependency context to inspect real usage.

## Output

Rank findings by biggest useful cut:

`<tag> <what to cut>. <replacement>. [path]`

Use the same tags as `ponytail-review`: `delete`, `stdlib`, `native`, `yagni`, `shrink`.

End with `net: -<N> lines, -<M> deps possible.` If nothing should be cut: `Lean already. Ship.`

## Workflow

Hunt for dependencies the platform already replaces, single-implementation interfaces, factories with one product, wrappers that only delegate, dead flags/config, speculative layers, needless one-export files, and hand-rolled standard-library behavior.

## Rules

- Repo-wide audit only; one-shot.
- Scope is over-engineering and complexity. Correctness, security, and performance belong in normal review.
- Report findings; do not mutate the repository unless the user separately asks.