Ponytail Audit Agent Skill
Audit the whole repo for over-engineering. A ranked list of what to delete, simplify, or replace with stdlib or native features.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/DietrichGebert/ponytail --skill ponytail-auditThe instruction itself
4 sections, as written by the authorponytail-review, repo-wide. Scan the whole tree instead of a diff. Rank
findings biggest cut first.
Tags
Same as ponytail-review:
delete:dead code, unused flexibility, speculative feature. Replacement: nothing.stdlib:hand-rolled thing the standard library ships. Name the function.native:dependency or code doing what the platform already does. Name the feature.yagni:abstraction with one implementation, config nobody sets, layer with one caller.shrink:same logic, fewer lines. Show the shorter form.
Hunt
Deps the stdlib or platform already ships, single-implementation interfaces,
factories with one product, wrappers that only delegate, files exporting one
thing, dead flags and config, hand-rolled stdlib.
Output
One line per finding, ranked: <tag> <what to cut>. <replacement>. [path].
End with net: -<N> lines, -<M> deps possible. Nothing to cut: Lean already. Ship.
Boundaries
Scope: over-engineering and complexity only. Correctness bugs, security holes,
and performance are explicitly out of scope. Route them to a normal review
pass. Lists findings, applies nothing. One-shot.
"stop ponytail-audit" or "normal mode" to revert.
Other skills for the same job
different authors, same section of the catalogue
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation
Use when completing tasks, implementing major features, or before merging to verify work meets requirements
Execute git commit with conventional commit message analysis, intelligent staging, and message generation. Use when user asks to commit changes, create a git commit, or mentions "/commit". Supports: (1) Auto-detecting type and scope from changes, (2) Generating conventional commit messages from diff, (3) Interactive commit with optional type/scope/description overrides, (4) Intelligent file staging for logical grouping
Comprehensive GitHub code review with AI-powered swarm coordination
Behavioral guidelines to reduce common LLM coding mistakes. Use when writing, reviewing, or refactoring code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
Use this skill to review code. It supports both local changes (staged or working tree) and remote Pull Requests (by ID or URL). It focuses on correctness, maintainability, and adherence to project standards.
Refactor bloated AGENTS.md, CLAUDE.md, or similar agent instruction files to follow progressive disclosure principles. Splits monolithic files into organized, linked documentation.
Create high-quality git commits: review/stage intended changes, split into logical commits, and write clear commit messages (including Conventional Commits). Use when the user asks to commit, craft a commit message, stage changes, or split work into multiple commits.
How to use it
Take dietrichgebert/ponytail-audit from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.