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
Install / Use
npx skills add DietrichGebert/ponytail --skill ponytail-reviewInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Development & EngineeringSupported Platforms
Our assessment of ponytail-review
ponytail-review scores 78/100 on our quality scale, 495th of 1,453 Development & Engineering skills we index (top 35%).
Its SKILL.md is 2.3 KB long, split into 4 sections and no code examples: moderately detailed.
With 145,162 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 10 days ago, so ponytail-review is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
ponytail-review compared with similar skills
All 4 of these similar skills score higher than ponytail-review; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| ponytail-review (this skill)by DietrichGebert | 78 | 145.2k | 10d ago | SKILL.md |
| ai-job-searchby MadsLorentzen | 100 | 43.9k | 3d ago | CLAUDE.md |
| claude-howtoby luongnv89 | 100 | 41.7k | 5d ago | CLAUDE.md |
| algorithmic-artby anthropics | 100 | 177.9k | 2d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 2d ago | SKILL.md |
Frequently asked questions
- How do I install ponytail-review?
- Run
npx skills add DietrichGebert/ponytail --skill ponytail-review. The install tabs above show the steps for each supported agent. - Which AI agents does ponytail-review work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is ponytail-review safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is ponytail-review still maintained?
- The repository was last updated 10 days ago, so ponytail-review is actively maintained.
Skill content
View source on GitHubname: ponytail-review description: > 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.
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.
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
