Skills / code-review / Alternatives

Testing · 12 alternatives

code-review alternatives.

code-review is review the changes since a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (does the code follow this repo's documented coding standards?) and Spec (does the code match what the originating issue/spec asked for?). Runs both reviews in parallel sub-agents and reports them side by side. Use when the user wants to review a branch, a PR, work-in-progress changes, or asks to…. Below are the other testing skills in the directory, with the 8 that have a published proof first. A proof means the skill was run on a fixed brief with and without it and both results are online, so you can judge the output rather than the star count.

Who should choose what

Start with the proven ones.

skill-creator, writing-guidelines, receiving-code-review, systematic-debugging, test-driven-development, differential-review, grilling, tdd have proofs you can open now. If you want evidence before installing, pick from those. If you need something more specific to your stack, the rest of the list is ranked by how widely the source repository is used. code-review does not have a proof yet; its author can order one for $49.

The list

12 skills compared.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Source anthropics/skillsLicense Not stated

Review docs/prose for Writing Guidelines compliance. Use when asked to "review my docs", "check writing style", "audit prose", "review docs voice and tone", or "check this page against the writing handbook".

Source vercel-labs/agent-skillsLicense Not stated

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

Source obra/superpowersLicense MIT

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

Source obra/superpowersLicense MIT

Use when implementing any feature or bugfix, before writing implementation code

Source obra/superpowersLicense MIT

Performs security-focused differential review of code changes. Adapts analysis depth to codebase size, uses git blame for context, calculates blast radius by counting callers, checks test coverage of modified code, and generates a markdown report. Use when reviewing a PR, commit, or diff for security vulnerabilities, checking whether a change re-introduces a previously fixed bug, asking what else…

Source trailofbits/skillsLicense Other
7

grilling

Proven

Grill the user relentlessly about a plan, decision, or idea. Use when the user wants to stress-test their thinking, or uses any 'grill' trigger phrases.

Source mattpocock/skillsLicense MIT
8

tdd

Proven

Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.

Source mattpocock/skillsLicense MIT

Audit REA CI and test suites for correctness, fixture drift, false passes, and measured performance; use for suite or workflow investigations and efficiency changes, rather than ordinary feature testing or a single test failure.

Source morluto/reaLicense MIT

Use when implementation is complete, all tests pass, and you need to decide how to integrate the work

Source obra/superpowersLicense MIT

Use when completing tasks, implementing major features, or before merging to verify work meets requirements

Source obra/superpowersLicense MIT

Use after generating code, after accepting AI suggestions, or when reviewing AI-written modules. Also use when code works but feels brittle, when error handling seems thin, when orphaned resources or missing cleanup are suspected, or when the agent claims done but hidden debt may exist. Catches the specific failure patterns AI agents produce that humans would not.

Source wshobson/agentsLicense MIT

Skills belong to their authors. Descriptions are taken from each SKILL.md, star counts from the source repository, and nothing here is paid placement. See the whole category: best testing skills.