backend-code-review — for Claude Code backend-code-review, official, for Claude Code, ide skills, agentic-ai, agentic-framework, agentic-workflow, gemini, low-code, nextjs

Verified
v1.0.0

À propos de ce Skill

Scenario recommande : Ideal for AI agents that need backend code review. Resume localise : Review backend code for quality, security, maintainability, and best practices based on established checklist rules. It covers agent, agentic-ai, agentic-framework workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Fonctionnalités

Backend Code Review
When to use this skill
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.

# Core Topics

langgenius langgenius
[139.2k]
[21822]
Updated: 4/26/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 11/11

This page remains useful for teams, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution Quality floor passed for review
Review Score
11/11
Quality Score
100
Canonical Locale
en
Detected Body Locale
en

Scenario recommande : Ideal for AI agents that need backend code review. Resume localise : Review backend code for quality, security, maintainability, and best practices based on established checklist rules. It covers agent, agentic-ai, agentic-framework workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

Pourquoi utiliser cette compétence

Recommandation : backend-code-review helps agents backend code review. Review backend code for quality, security, maintainability, and best practices based on established checklist rules. This AI agent skill supports

Meilleur pour

Scenario recommande : Ideal for AI agents that need backend code review.

Cas d'utilisation exploitables for backend-code-review

Cas d'usage : Applying Backend Code Review
Cas d'usage : Applying When to use this skill
Cas d'usage : Applying Do NOT use this skill when:

! Sécurité et Limitations

  • Limitation : Do NOT use this skill when:
  • Limitation : Do NOT use this skill when: The request is about frontend code or UI (e.g., .tsx, .ts, .js, web/)
  • Limitation : Keep the scope tight: review only what the user provided or explicitly referenced

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Curated Collection Review

Reviewed In Curated Collections

This section shows how Killer-Skills includes, reviews, and maintains this skill inside curated collections, so you can see where it fits in practical selection paths instead of relying only on the upstream README.

Reviewed Collection

12 outils d’agents IA propulsés par OpenAI | AI Agent Skills

Reviewed 2026-04-17

Reviewed on 2026-04-17 for setup clarity, eval usefulness, runtime visibility, and maintainer reliability. We kept the tools that help OpenAI teams move from experiments to repeatable production routines.

OpenAI visitors usually arrive with a concrete job: improve prompts, add evals, debug runtime behavior, or make agent operations easier to hand off. This page narrows the shortlist around those jobs.

12 entries Killer-Skills curation review with monthly collection checks.
Reviewed Collection

outils IA Next.js pour workflows full-stack | AI Agent Skills

Reviewed 2026-04-17

Reviewed on 2026-04-17 against Next.js workflow fit, installation clarity, team adoption, and full-stack delivery usefulness. This page is now positioned as an installation-focused Next.js entry point instead of a broad framework roundup.

We prioritize this page because Next.js-intent users usually need a shortlist they can install, validate, and carry into real full-stack release loops quickly.

12 entries Maintained through Killer-Skills curation review with trust, install-path, and setup checks.
Reviewed Collection

outils d'agents IA Python pour les workflows dev | AI Agent Skills

Reviewed 2026-04-17

Reviewed on 2026-04-17 against Python workflow fit, installation clarity, team adoption, and day-to-day engineering usefulness. This page is now positioned as an installation-focused Python entry point instead of a broad language roundup.

We prioritize this page because Python-intent users usually need a shortlist they can install, validate, and carry into real automation and delivery loops quickly.

12 entries Maintained through Killer-Skills curation review with install, documentation, and Python workflow checks.
After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is backend-code-review?

Scenario recommande : Ideal for AI agents that need backend code review. Resume localise : Review backend code for quality, security, maintainability, and best practices based on established checklist rules. It covers agent, agentic-ai, agentic-framework workflows. This AI agent skill supports Claude Code, Cursor, and Windsurf workflows.

How do I install backend-code-review?

Run the command: npx killer-skills add langgenius/dify. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for backend-code-review?

Key use cases include: Cas d'usage : Applying Backend Code Review, Cas d'usage : Applying When to use this skill, Cas d'usage : Applying Do NOT use this skill when:.

Which IDEs are compatible with backend-code-review?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for backend-code-review?

Limitation : Do NOT use this skill when:. Limitation : Do NOT use this skill when: The request is about frontend code or UI (e.g., .tsx, .ts, .js, web/). Limitation : Keep the scope tight: review only what the user provided or explicitly referenced.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add langgenius/dify. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use backend-code-review immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

backend-code-review

Install backend-code-review, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

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 outside api/).

How to use this skill

Follow these steps when using this skill:

  1. 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.
  2. 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.
  3. 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:Line references 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/ or api/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 under api/repositories, api/core/repositories, or api/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)

markdown
1# Code Review Summary 2 3Found <X> critical issues need to be fixed: 4 5## 🔴 Critical (Must Fix) 6 7### 1. <brief description of the issue> 8 9FilePath: <path> line <line> 10<relevant code snippet or pointer> 11 12#### Explanation 13 14<detailed explanation and references of the issue> 15 16#### Suggested Fix 17 181. <brief description of suggested fix> 192. <code example> (optional, omit if not applicable) 20 21--- 22... (repeat for each critical issue) ... 23 24Found <Y> suggestions for improvement: 25 26## 🟡 Suggestions (Should Consider) 27 28### 1. <brief description of the suggestion> 29 30FilePath: <path> line <line> 31<relevant code snippet or pointer> 32 33#### Explanation 34 35<detailed explanation and references of the suggestion> 36 37#### Suggested Fix 38 391. <brief description of suggested fix> 402. <code example> (optional, omit if not applicable) 41 42--- 43... (repeat for each suggestion) ... 44 45Found <Z> optional nits: 46 47## 🟢 Nits (Optional) 48### 1. <brief description of the nit> 49 50FilePath: <path> line <line> 51<relevant code snippet or pointer> 52 53#### Explanation 54 55<explanation and references of the optional nit> 56 57#### Suggested Fix 58 59- <minor suggestions> 60 61--- 62... (repeat for each nits) ... 63 64## ✅ What's Good 65 66- <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)

markdown
1## Code Review Summary 2✅ No issues found.

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