backend-code-review▌
langgenius/dify · updated May 23, 2026
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Use this skill whenever the user asks to review, analyze, or improve backend code (e.g., .py) under the api/ directory. Supports the following review modes:
Backend Code Review
When to use this skill
Use this skill whenever the user asks to review, analyze, or improve backend code (e.g., .py) under the api/ directory. Supports the following review modes:
- Pending-change review: when the user asks to review current changes (inspect staged/working-tree files slated for commit to get the changes).
- Code snippets review: when the user pastes code snippets (e.g., a function/class/module excerpt) into the chat and asks for a review.
- File-focused review: when the user points to specific files and asks for a review of those files (one file or a small, explicit set of files, e.g.,
api/...,api/app.py).
Do NOT use this skill when:
- The request is about frontend code or UI (e.g.,
.tsx,.ts,.js,web/). - The user is not asking for a review/analysis/improvement of backend code.
- The scope is not under
api/(unless the user explicitly asks to review backend-related changes outsideapi/).
How to use this skill
Follow these steps when using this skill:
- Identify the review mode (pending-change vs snippet vs file-focused) based on the user’s input. Keep the scope tight: review only what the user provided or explicitly referenced.
- Follow the rules defined in Checklist to perform the review. If no Checklist rule matches, apply General Review Rules as a fallback to perform the best-effort review.
- Compose the final output strictly follow the Required Output Format.
Notes when using this skill:
- Always include actionable fixes or suggestions (including possible code snippets).
- Use best-effort
File:Linereferences when a file path and line numbers are available; otherwise, use the most specific identifier you can.
Checklist
- db schema design: if the review scope includes code/files under
api/models/orapi/migrations/, follow references/db-schema-rule.md to perform the review - architecture: if the review scope involves controller/service/core-domain/libs/model layering, dependency direction, or moving responsibilities across modules, follow references/architecture-rule.md to perform the review
- repositories abstraction: if the review scope contains table/model operations (e.g.,
select(...),session.execute(...), joins, CRUD) and is not underapi/repositories,api/core/repositories, orapi/extensions/*/repositories/, follow references/repositories-rule.md to perform the review - sqlalchemy patterns: if the review scope involves SQLAlchemy session/query usage, db transaction/crud usage, or raw SQL usage, follow references/sqlalchemy-rule.md to perform the review
General Review Rules
1. Security Review
Check for:
- SQL injection vulnerabilities
- Server-Side Request Forgery (SSRF)
- 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
- Memory leaks
- Blocking operations in async code
- Missing caching opportunities
3. Code Quality Review
Check for:
- Code forward compatibility
- 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
Required Output Format
When this skill invoked, the response must exactly follow one of the two templates:
Template A (any findings)
# Code Review Summary
Found <X> critical issues need to be fixed:
## 🔴 Critical (Must Fix)
### 1. <brief description of the issue>
FilePath: <path> line <line>
<relevant code snippet or pointer>
#### Explanation
<detailed explanation and references of the issue>
#### Suggested Fix
1. <brief description of suggested fix>
2. <code example> (optional, omit if not applicable)
---
... (repeat for each critical issue) ...
Found <Y> suggestions for improvement:
## 🟡 Suggestions (Should Consider)
### 1. <brief description of the suggestion>
FilePath: <path> line <line>
<relevant code snippet or pointer>
#### Explanation
<detailed explanation and references of the suggestion>
#### Suggested Fix
1. <brief description of suggested fix>
2. <code example> (optional, omit if not applicable)
---
... (repeat for each suggestion) ...
Found <Z> optional nits:
## 🟢 Nits (Optional)
### 1. <brief description of the nit>
FilePath: <path> line <line>
<relevant code snippet or pointer>
#### Explanation
<explanation and references of the optional nit>
#### Suggested Fix
- <minor suggestions>
---
... (repeat for each nits) ...
## ✅ What's Good
- <Positive feedback on good patterns>
- If there are no critical issues or suggestions or option nits or good points, just omit that section.
- If the issue number is more than 10, summarize as "Found 10+ critical issues/suggestions/optional nits" and only output the first 10 items.
- Don't compress the blank lines between sections; keep them as-is for readability.
- If there is any issue requires code changes, append a brief follow-up question to ask whether the user wants to apply the fix(es) after the structured output. For example: "Would you like me to use the Suggested fix(es) to address these issues?"
Template B (no issues)
## Code Review Summary
✅ No issues found.
How to use backend-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 backend-code-review
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches backend-code-review from GitHub repository langgenius/dify 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 backend-code-review. Access the skill through slash commands (e.g., /backend-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
4.7★★★★★64 reviews- ★★★★★Noor Malhotra· Dec 24, 2024
Keeps context tight: backend-code-review is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Aisha Gill· Dec 20, 2024
backend-code-review has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Aisha Ghosh· Dec 16, 2024
backend-code-review is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Diego Flores· Dec 16, 2024
backend-code-review reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Ganesh Mohane· Dec 4, 2024
Useful defaults in backend-code-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Sakshi Patil· Nov 23, 2024
backend-code-review is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Anaya Yang· Nov 23, 2024
backend-code-review reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Diego Singh· Nov 15, 2024
Registry listing for backend-code-review matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Aarav Bansal· Nov 15, 2024
I recommend backend-code-review for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Zaid Abbas· Nov 11, 2024
backend-code-review fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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