code-review▌
skillcreatorai/ai-agent-skills · updated Apr 8, 2026
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Automated code review across security, performance, quality, and testing dimensions.
- ›Analyzes pull requests for four distinct review categories: security vulnerabilities (SQL injection, XSS, hardcoded secrets), performance issues (N+1 queries, memory leaks, missing caches), code quality (duplication, SRP violations, poor naming), and test coverage gaps
- ›Flags issues at three severity levels (critical, suggestions, nits) with explanations and suggested fixes for each finding
- ›Includes a
Code Review
Review Categories
1. Security Review
Check for:
- SQL injection vulnerabilities
- XSS (Cross-Site Scripting)
- Command injection
- Insecure deserialization
- Hardcoded secrets/credentials
- Improper authentication/authorization
- Insecure direct object references
2. Performance Review
Check for:
- N+1 queries
- Missing database indexes
- Unnecessary re-renders (React)
- Memory leaks
- Blocking operations in async code
- Missing caching opportunities
- Large bundle sizes
3. Code Quality Review
Check for:
- Code duplication (DRY violations)
- Functions doing too much (SRP violations)
- Deep nesting / complex conditionals
- Magic numbers/strings
- Poor naming
- Missing error handling
- Incomplete type coverage
4. Testing Review
Check for:
- Missing test coverage for new code
- Tests that don't test behavior
- Flaky test patterns
- Missing edge cases
- Mocked external dependencies
Review Output Format
## Code Review Summary
### 🔴 Critical (Must Fix)
- **[File:Line]** [Issue description]
- **Why:** [Explanation]
- **Fix:** [Suggested fix]
### 🟡 Suggestions (Should Consider)
- **[File:Line]** [Issue description]
- **Why:** [Explanation]
- **Fix:** [Suggested fix]
### 🟢 Nits (Optional)
- **[File:Line]** [Minor suggestion]
### ✅ What's Good
- [Positive feedback on good patterns]
Common Patterns to Flag
Security
// BAD: SQL injection
const query = `SELECT * FROM users WHERE id = ${userId}`;
// GOOD: Parameterized query
const query = 'SELECT * FROM users WHERE id = $1';
await db.query(query, [userId]);
Performance
// BAD: N+1 query
users.forEach(async user => {
const posts = await getPosts(user.id);
});
// GOOD: Batch query
const userIds = users.map(u => u.id);
const posts = await getPostsForUsers(userIds);
Error Handling
// BAD: Swallowing errors
try {
await riskyOperation();
} catch (e) {}
// GOOD: Handle or propagate
try {
await riskyOperation();
} catch (e) {
logger.error('Operation failed', { error: e });
throw new AppError('Operation failed', { cause: e });
}
Review Checklist
- No hardcoded secrets
- Input validation present
- Error handling complete
- Types/interfaces defined
- Tests added for new code
- No obvious performance issues
- Code is readable and documented
- Breaking changes documented
How to use code-review on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add code-review
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches code-review from GitHub repository skillcreatorai/ai-agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate code-review. Access the skill through slash commands (e.g., /code-review) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★33 reviews- ★★★★★Chen Malhotra· Dec 24, 2024
code-review has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Chaitanya Patil· Dec 8, 2024
Solid pick for teams standardizing on skills: code-review is focused, and the summary matches what you get after install.
- ★★★★★Piyush G· Nov 27, 2024
We added code-review from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Alexander Thompson· Nov 15, 2024
code-review fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Rahul Santra· Nov 7, 2024
I recommend code-review for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Alexander Abebe· Nov 7, 2024
I recommend code-review for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Pratham Ware· Oct 26, 2024
Useful defaults in code-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Li White· Oct 26, 2024
Useful defaults in code-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Shikha Mishra· Oct 18, 2024
code-review fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Sofia Chawla· Oct 6, 2024
We added code-review from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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