ponytail-review

Reviews code diffs for over-engineering and lists what to delete or simplify.

Updated Aug 7, 2026
One-click install
npx skills add https://github.com/Sambhav242005/Major-Project --skill ponytail-review-sambhav242005
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ponytail-review
Source: https://github.com/Sambhav242005/Major-Project/tree/main/.agents/skills/ponytail-review
Command: npx skills add https://github.com/Sambhav242005/Major-Project --skill ponytail-review-sambhav242005

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Codebases accumulate unnecessary complexity: hand-rolled utilities that duplicate the standard library, speculative abstractions with a single implementation, and dependencies that add nothing. This Skill reviews diffs exclusively for over-engineering and tells you exactly what to cut, keeping reviews focused and actionable. ## Core Features & Use Cases - Complexity-Only Review: Hunts dead code, reinvented stdlib functionality, unneeded dependencies, and speculative abstractions while explicitly excluding correctness, security, and performance concerns. - One-Line Findings: Each finding uses a compact tagged format (delete, stdlib, native, yagni, shrink) with location, what to cut, and what replaces it. - Net-Line Scoring: Ends every review with a single metric estimating how many lines the diff could lose. - Use Case: Before merging a pull request that adds a custom retry wrapper, an abstract repository with one implementation, and a moment.js import, run this review to get findings like "L4: native: moment.js imported for one format call. Intl.DateTimeFormat, 0 deps." ## Quick Start Ask the AI to review this diff for over-engineering and tell me what can be deleted.

Frequently Asked Questions about ponytail-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I review code for over-engineering?▼

Invoke the review on a diff and it returns one line per finding: location, a tag (delete, stdlib, native, yagni, shrink), what to cut, and what replaces it. It ends with a net line-reduction estimate so you can judge the simplification potential.

What kinds of complexity does an over-engineering review find?▼

It finds hand-rolled code the standard library already ships, dependencies duplicating native platform features, abstractions with a single implementation, dead code, and logic that can be expressed in fewer lines.

Does this review catch bugs or security issues?▼

No. Correctness bugs, security holes, and performance problems are explicitly out of scope and should be routed to a normal review pass. This review only hunts unnecessary complexity.

Will the review apply the suggested deletions automatically?▼

No. It only lists findings with locations and replacements; it never modifies the code. You decide which suggestions to apply in a separate editing step.

When should I not use an over-engineering review?▼

Skip it when a diff needs correctness, security, or performance validation, since those are out of scope. It also never flags minimal smoke tests or assert-based self-checks, which it treats as the acceptable minimum.