fastapi-code-review▌
existential-birds/beagle · updated May 12, 2026
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These are idiomatic FastAPI patterns that may appear problematic but are correct:
FastAPI Code Review
Quick Reference
| Issue Type | Reference |
|---|---|
| APIRouter setup, response_model, status codes | references/routes.md |
| Depends(), yield deps, cleanup, shared deps | references/dependencies.md |
| Pydantic models, HTTPException, 422 handling | references/validation.md |
| Async handlers, blocking I/O, background tasks | references/async.md |
Review Checklist
- APIRouter with proper prefix and tags
- All routes specify
response_modelfor type safety - Correct HTTP methods (GET, POST, PUT, DELETE, PATCH)
- Proper status codes (200, 201, 204, 404, etc.)
- Dependencies use
Depends()not manual calls - Yield dependencies have proper cleanup
- Request/Response models use Pydantic
- HTTPException with status code and detail
- All route handlers are
async def - No blocking I/O (
requests,time.sleep,open()) - Background tasks for non-blocking operations
- No bare
exceptin route handlers
Valid Patterns (Do NOT Flag)
These are idiomatic FastAPI patterns that may appear problematic but are correct:
- Pydantic validates request body automatically - No manual validation needed when using typed Pydantic models as parameters
- Dependency injection for database sessions - Sessions come from
Depends(), not passed as function arguments - HTTPException for all HTTP errors - FastAPI handles conversion to proper HTTP responses
- Async def endpoint without await - May be using sync dependencies or simple operations; FastAPI handles this
- Type annotation on Depends() - This is documentation/IDE support, not a type assertion
- Query/Path/Body defaults - FastAPI processes these at runtime, not traditional Python defaults
- Returning dict from endpoint - Pydantic converts automatically if
response_modelis set
Context-Sensitive Rules
Only flag issues when the context warrants it:
- Flag missing validation ONLY IF the field isn't already in a Pydantic model with validators
- Flag missing auth ONLY IF the endpoint isn't using
Depends()with an auth dependency - Flag missing error handling ONLY IF HTTPException isn't raised appropriately for error cases
- Flag sync in async ONLY IF the operation is actually blocking (file I/O, network calls, CPU-bound), not just non-async
FastAPI Framework Behaviors
FastAPI + Pydantic handle many concerns automatically:
- Request validation via Pydantic models
- Response serialization via response_model
- Dependency injection for cross-cutting concerns
- Exception handling via exception handlers
Before flagging "missing" functionality, verify FastAPI isn't handling it.
When to Load References
- Reviewing route definitions → routes.md
- Reviewing dependency injection → dependencies.md
- Reviewing Pydantic models/validation → validation.md
- Reviewing async route handlers → async.md
Review Questions
- Do all routes have explicit response models and status codes?
- Are dependencies injected via Depends() with proper cleanup?
- Do all Pydantic models validate inputs correctly?
- Are all route handlers async and non-blocking?
Before Submitting Findings
Load and follow review-verification-protocol before reporting any issue.
How to use fastapi-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 fastapi-code-review
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches fastapi-code-review from GitHub repository existential-birds/beagle 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 fastapi-code-review. Access the skill through slash commands (e.g., /fastapi-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▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★49 reviews- ★★★★★Hana Mensah· Dec 28, 2024
fastapi-code-review is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Diya Mehta· Dec 24, 2024
Registry listing for fastapi-code-review matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Harper Liu· Dec 20, 2024
We added fastapi-code-review from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Meera Perez· Dec 16, 2024
Useful defaults in fastapi-code-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Meera Dixit· Dec 4, 2024
fastapi-code-review fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Oshnikdeep· Nov 27, 2024
fastapi-code-review has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Diya Menon· Nov 19, 2024
fastapi-code-review reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Rahul Santra· Nov 15, 2024
We added fastapi-code-review from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Sophia Jain· Nov 15, 2024
Keeps context tight: fastapi-code-review is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Ishan Gonzalez· Nov 7, 2024
fastapi-code-review has been reliable in day-to-day use. Documentation quality is above average for community skills.
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