- Home
- Skills
- Onewave Ai
- Claude Skills
- Code Review Pro
code-review-pro_skill
- Python
36
GitHub Stars
1
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill onewave-ai/claude-skills --skill code-review-pro- SKILL.md5.1 KB
Overview
This skill performs comprehensive code reviews focused on security vulnerabilities, performance bottlenecks, maintainability issues, and refactoring opportunities. It produces prioritized, actionable findings with before/after code examples and clear remediation steps. Use it to get a practical audit of code quality, risks, and quick wins.
How this skill works
I inspect source code and related config for common and language-specific risks: injection vectors, auth flaws, unsafe dependencies, inefficient algorithms, memory and I/O issues, and maintainability smells. I prioritize issues by severity, show concrete code changes (before/after), and recommend tests, monitoring, or architecture adjustments. Reports highlight critical fixes first, followed by performance, quality, and nice-to-have improvements.
When to use it
- When you ask for a code review or audit
- Before shipping security-sensitive features (auth, payments, data export)
- When tracking down performance regressions or latency spikes
- Before major refactors or production rollouts
- When onboarding a new codebase and validating quality
Best practices
- Prioritize security issues first and fix high-severity bugs immediately
- Provide small, testable code changes with before/after examples
- Include line references and reproduce steps where possible
- Favor parameterized queries, proper input validation, and secure secret management
- Measure performance impact of fixes with benchmarks or profiling
- Balance refactoring scope: prefer incremental improvements and quick wins
Example use cases
- Review an authentication module for weak hashing, token handling, and CSRF issues
- Audit a database access layer for SQL injection, N+1 queries, and missing indexes
- Optimize a React/Vue component to remove unnecessary re-renders and reduce bundle size
- Analyze an API endpoint for input validation, error handling, and rate limiting
- Suggest refactors to reduce cyclomatic complexity and duplicate logic
FAQ
I focus on common stacks and idioms; Python is primary, and I cover JavaScript frameworks, backend APIs, and SQL patterns with language-specific recommendations.
How are findings prioritized?
Findings are prioritized by impact and exploitability: Critical security issues first, then high performance or reliability risks, then maintainability and style items.
Will you provide code fixes I can apply directly?
Yes. Each actionable issue includes a before/after snippet and an explanation. For large changes I propose incremental steps and tests.