YaroslavKomarov/ai-factory.review
.claude/skills/review/SKILL.md
Perform code review on staged changes or a pull request. Checks for bugs, security issues, performance problems, and best practices. Use when user says "review code", "check my code", "review PR", or "is this code okay".
development
Updated Apr 16, 2026
$ install --global
skillsauthnpx skillsauth add YaroslavKomarov/ShedulerBot ai-factory.reviewInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 16, 2026, 8:33 PM4.5s1 file scanned
SKILL.md
- name:
- ai-factory.review
- description:
- Perform code review on staged changes or a pull request. Checks for bugs, security issues, performance problems, and best practices. Use when user says "review code", "check my code", "review PR", or "is this code okay".
- argument-hint:
- [PR number or empty]
- allowed-tools:
- Bash(git *) Bash(gh *) Read Glob Grep
Code Review Assistant
Perform thorough code reviews focusing on correctness, security, performance, and maintainability.
Behavior
Without Arguments (Review Staged Changes)
- Run
git diff --cachedto get staged changes - If nothing staged, run
git difffor unstaged changes - Analyze each file's changes
With PR Number/URL
- Use
gh pr view <number> --jsonto get PR details - Use
gh pr diff <number>to get the diff - Review all changes in the PR
Review Checklist
Correctness
- [ ] Logic errors or bugs
- [ ] Edge cases handling
- [ ] Null/undefined checks
- [ ] Error handling completeness
- [ ] Type safety (if applicable)
Security
- [ ] SQL injection vulnerabilities
- [ ] XSS vulnerabilities
- [ ] Command injection
- [ ] Sensitive data exposure
- [ ] Authentication/authorization issues
- [ ] CSRF protection
- [ ] Input validation
Performance
- [ ] N+1 query problems
- [ ] Unnecessary re-renders (React)
- [ ] Memory leaks
- [ ] Inefficient algorithms
- [ ] Missing indexes (database)
- [ ] Large payload sizes
Best Practices
- [ ] Code duplication
- [ ] Dead code
- [ ] Magic numbers/strings
- [ ] Proper naming conventions
- [ ] SOLID principles
- [ ] DRY principle
Testing
- [ ] Test coverage for new code
- [ ] Edge cases tested
- [ ] Mocking appropriateness
Output Format
## Code Review Summary
**Files Reviewed:** [count]
**Risk Level:** 🟢 Low / 🟡 Medium / 🔴 High
### Critical Issues
[Must be fixed before merge]
### Suggestions
[Nice to have improvements]
### Questions
[Clarifications needed]
### Positive Notes
[Good patterns observed]
Review Style
- Be constructive, not critical
- Explain the "why" behind suggestions
- Provide code examples when helpful
- Acknowledge good code
- Prioritize feedback by importance
- Ask questions instead of making assumptions
Examples
User: /ai-factory.review
Review staged changes in current repository.
User: /ai-factory.review 123
Review PR #123 using GitHub CLI.
User: /ai-factory.review https://github.com/org/repo/pull/123
Review PR from URL.
Integration
If GitHub MCP is configured, can:
- Post review comments directly to PR
- Request changes or approve
- Add labels based on review outcome
Tip: Context is heavy after code review. Consider
/clearor/compactbefore continuing with other tasks.
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