code-review-pro

Featured

Performs a deep code review of files, modules, a diff, or a branch - finding security vulnerabilities (mapped to OWASP Top 10:2025), correctness bugs, performance problems, and maintainability issues - and returns severity-ranked findings with evidence and concrete fixes. Use when the user asks to review, audit, or sanity-check code, asks "is this safe", "what's wrong with this", "find bugs", or wants a security or performance pass before shipping. For posting line comments on a GitHub pull request, use git-pr-reviewer.

Code & Development 307 stars 53 forks Updated 3 days ago MIT

Install

View on GitHub

Quality Score: 90/100

Stars 20%
83
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Code Review Pro Find the problems that matter, prove each one, and show the fix. A short list of real issues beats a long list of maybes. ## Workflow 1. **Set the scope.** Decide what is under review: a pasted snippet, specific files, the working-tree diff (`git diff`, `git diff --staged`), or a branch against its base (`git diff main...HEAD`). For a diff, review the changed lines but read enough surrounding code to know how they are called. 2. **Learn the context before judging.** Identify language, framework and version (check `package.json`, `pyproject.toml`, `go.mod`, and so on), how the code is reached (HTTP handler, job, CLI, library), what input is untrusted, and any repo conventions (linters, `CLAUDE.md`, existing patterns). A pattern that is a bug in one framework can be safe in another; for example, React escapes JSX text, so XSS lives in `dangerouslySetInnerHTML`, `href` values, and raw HTML sinks. 3. **Review in priority order**, using [references/checklist.md](references/checklist.md): 1. Security 2. Correctness and edge cases 3. Performance 4. Maintainability and conventions 4. **Verify every finding before reporting it.** For each candidate, trace the data flow: where does the input come from, can an attacker or real user control it, and does anything upstream already validate or escape it? Check whether a test covers it. If you can run code, reproduce the bug with a small test or script. Drop findings you cannot support; mark the rest with ...

Details

Author
OneWave-AI
Repository
OneWave-AI/claude-skills
Created
11 months ago
Last Updated
3 days ago
Language
Python
License
MIT

Integrates with

Similar Skills

Semantically similar based on skill content — not just same category