agentleFS
kazemcodeskazemcodes/skill-tree/skills/ponytail-review/SKILL.md

ponytail-review

Skill1 starsChanged 5 months agoMITView on GitHub

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.

72 other projects use a version of this, 18 of them edited.

Adopted by

Most recently taken up by

Used with

Projects with it also use caveman-explore, migration and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • JuliusBrusseeSkill

    caveman-explore

    Read-only repository explorer for cold-start orientation, broad cross-file localization, or when a direct search failed. Skip it when the exact file or symbol is already named. Returns path:line citations only; its reads stay out of main context.

    Also in 4 projects that use this

  • ryu111Skill

    migration

    Migration planning expertise. Use when replacing tools/frameworks, upgrading versions, migrating databases, or planning transitions. Contains strategies, compatibility analysis methods, and rollback planning.

    Also in 5 projects that use this

  • JuliusBrusseeSkill

    surgical-patch

    Fix bugs and small behavior changes at the narrowest responsible layer. Use when regression proof, preserved surrounding behavior, and task-relevant tests matter.

    Also in 3 projects that use this

  • huangzidaSkill

    caveman-help

    Quick-reference card for all caveman modes, skills, and commands. One-shot display, not a persistent mode. Trigger: /caveman-help, "caveman help", "what caveman commands", "how do I use caveman".

    Also in 6 projects that use this

  • huangzidaSkill

    caveman-compress

    Compress natural language memory files (CLAUDE.md, todos, preferences) into caveman format to save input tokens. Preserves all technical substance, code, URLs, and structure. Compressed version overwrites the original file. Human-readable backup saved as FILE.original.md. Trigger: /caveman:compress <filepath> or "compress memory file"

    Also in 5 projects that use this

  • jaydubya818Skill

    thermo-nuclear-code-quality-review

    Use when the user requests an intentionally strict maintainability review.

    Also in 5 projects that use this

  • +2 more from JuliusBrussee
  • +2 more from huangzida

The file

We split this skill into the rules it gives an agent

2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 38 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    If there is nothing to cut, say Lean already.

    line 48
  2. Distinctive:

    Does not apply the fixes, only lists them.

    line 56

“Common” is measured: kept by at least 6 in 10 of the 38 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.