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Ponytail Review

CommunityPopular
DietrichGebert
ponytail-review

Code review focused exclusively on over-engineering. Finds what to delete: reinvented standard library, unneeded dependencies, speculative abstractions, dead flexibility. One line per finding: location, what to cut, what replaces it. Use when the user says "review for over-engineering", "what can we delete", "is this over-engineered", "simplify review", or invokes /ponytail-review. Complements correctness-focused review, this one only hunts complexity.

Overview

PublisherDietrichGebert
Repositoryponytail
Skill nameponytail-review
Stars
141.3K
Forks
7.6K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by DietrichGebert on GitHub. Read the source before you install it.

Installation

Install the Ponytail Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/DietrichGebert/ponytail.git /tmp/ponytail
mkdir -p .claude/skills
cp -r /tmp/ponytail/skills/ponytail-review .claude/skills/ponytail-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ponytail Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ponytail Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ponytail Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Review diffs for unnecessary complexity. One line per finding: location, what to cut, what replaces it. The diff's best outcome is getting shorter.

Format

L<line>: <tag> <what>. <replacement>., or <file>:L<line>: ... for multi-file diffs.

Tags:

  • 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.

Examples

❌ "This EmailValidator class might be more complex than necessary, have you considered whether all these validation rules are needed at this stage?"

L12-38: stdlib: 27-line validator class. "@" in email, 1 line, real validation is the confirmation mail.

L4: native: moment.js imported for one format call. Intl.DateTimeFormat, 0 deps.

repo.py:L88: yagni: AbstractRepository with one implementation. Inline it until a second one exists.

L52-71: delete: retry wrapper around an idempotent local call. Nothing replaces it.

L30-44: shrink: manual loop builds dict. dict(zip(keys, values)), 1 line.

Scoring

End with the only metric that matters: net: -<N> lines possible.

If there is nothing to cut, say Lean already. Ship. and stop.

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, not this one. A single smoke test or assert-based self-check is the ponytail minimum, not bloat, never flag it for deletion. Does not apply the fixes, only lists them. "stop ponytail-review" or "normal mode": revert to verbose review style.

Frequently asked questions

What does the Ponytail Review AI skill do?

Code review focused exclusively on over-engineering. Finds what to delete: reinvented standard library, unneeded dependencies, speculative abstractions, dead flexibility. One line per finding: location, what to cut, what replaces it. Use when the user says "review for over-engineering", "what can we delete", "is this over-engineered", "simplify review", or invokes /ponytail-review. Complements correctness-focused review, this one only hunts complexity.

Why use Ponytail Review on TypingMind?

Because you install it once and use it with any model. Ponytail Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ponytail Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/DietrichGebert/ponytail/tree/main/skills/ponytail-review. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ponytail Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ponytail Review?

As many as you like. As long as a model supports skills, you can use Ponytail Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ponytail Review AI skill free?

Yes. It is published on GitHub by DietrichGebert under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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