PO

ponytail-review

Identifies over-engineered code that can be simplified or deleted.

Install

mkdir -p .claude/skills/ponytail-review && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/13336" && unzip -o skill.zip -d .claude/skills/ponytail-review && rm skill.zip

Installs to .claude/skills/ponytail-review

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

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.
456 chars✓ has a “when” triggerlonger than Claude Code's old 250-char listing cap (fine on current versions)
Beginner

Key capabilities

  • Identify reinvented standard library functions
  • Flag unneeded dependencies
  • Detect speculative abstractions
  • Locate dead flexibility
  • Suggest simpler code forms

How it works

The skill analyzes code diffs to find instances of over-engineering. It provides specific suggestions for simplification, including what to remove and what to use instead.

Inputs & outputs

You give it
code diff
You get back
list of findings with location, what to cut, and what replaces it

When to use ponytail-review

  • Review for over-engineering
  • Simplify code logic
  • Delete unnecessary dependencies

About this skill

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.

When not to use it

  • When the request is for performance issues

Limitations

  • Does not address correctness bugs
  • Does not address security holes
  • Does not apply the fixes, only lists them

How it compares

This review focuses exclusively on over-engineering and complexity, providing a targeted review for simplification and reduction of code, unlike a general code review.

Compared to similar skills

ponytail-review side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
ponytail-review (this skill)01moNo flagsBeginner
effective-go3239moNo flagsBeginner
solid-principles579moNo flagsIntermediate
typescript-review392moNo flagsIntermediate

Try saying

Example prompts that trigger this skill in your AI assistant.

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