code-review▌
Donchitos/Claude-Code-Game-Studios · updated Apr 20, 2026
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### Code Review
- ›description: "Performs an architectural and quality code review on a specified file or set of files. Checks for coding standard compliance, architectural pattern adherence, SOLID principles, testabili
- ›argument-hint: "[path-to-file-or-directory]"
- ›allowed-tools: Read, Glob, Grep, Bash, Task
| name | code-review |
| description | "Performs an architectural and quality code review on a specified file or set of files. Checks for coding standard compliance, architectural pattern adherence, SOLID principles, testability, and performance concerns." |
| argument-hint | "[path-to-file-or-directory]" |
| user-invocable | true |
| allowed-tools | Read, Glob, Grep, Bash, Task |
| agent | lead-programmer |
Phase 1: Load Target Files
Read the target file(s) in full. Read CLAUDE.md for project coding standards.
Phase 2: Identify Engine Specialists
Read .claude/docs/technical-preferences.md, section ## Engine Specialists. Note:
- The Primary specialist (used for architecture and broad engine concerns)
- The Language/Code Specialist (used when reviewing the project's primary language files)
- The Shader Specialist (used when reviewing shader files)
- The UI Specialist (used when reviewing UI code)
If the section reads [TO BE CONFIGURED], no engine is pinned — skip engine specialist steps.
Phase 3: ADR Compliance Check
Search for ADR references in the story file, commit messages, and header comments. Look for patterns like ADR-NNN or docs/architecture/ADR-.
If no ADR references found, note: "No ADR references found — skipping ADR compliance check."
For each referenced ADR: read the file, extract the Decision and Consequences sections, then classify any deviation:
- ARCHITECTURAL VIOLATION (BLOCKING): Uses a pattern explicitly rejected in the ADR
- ADR DRIFT (WARNING): Meaningfully diverges from the chosen approach without using a forbidden pattern
- MINOR DEVIATION (INFO): Small difference from ADR guidance that doesn't affect overall architecture
Phase 4: Standards Compliance
Identify the system category (engine, gameplay, AI, networking, UI, tools) and evaluate:
- Public methods and classes have doc comments
- Cyclomatic complexity under 10 per method
- No method exceeds 40 lines (excluding data declarations)
- Dependencies are injected (no static singletons for game state)
- Configuration values loaded from data files
- Systems expose interfaces (not concrete class dependencies)
Phase 5: Architecture and SOLID
Architecture:
- Correct dependency direction (engine <- gameplay, not reverse)
- No circular dependencies between modules
- Proper layer separation (UI does not own game state)
- Events/signals used for cross-system communication
- Consistent with established patterns in the codebase
SOLID:
- Single Responsibility: Each class has one reason to change
- Open/Closed: Extendable without modification
- Liskov Substitution: Subtypes substitutable for base types
- Interface Segregation: No fat interfaces
- Dependency Inversion: Depends on abstractions, not concretions
Phase 6: Game-Specific Concerns
- Frame-rate independence (delta time usage)
- No allocations in hot paths (update loops)
- Proper null/empty state handling
- Thread safety where required
- Resource cleanup (no leaks)
Phase 7: Specialist Reviews (Parallel)
Spawn all applicable specialists simultaneously via Task — do not wait for one before starting the next.
Engine Specialists
If an engine is configured, determine which specialist applies to each file and spawn in parallel:
- Primary language files (
.gd,.cs,.cpp) → Language/Code Specialist - Shader files (
.gdshader,.hlsl, shader graph) → Shader Specialist - UI screen/widget code → UI Specialist
- Cross-cutting or unclear → Primary Specialist
Also spawn the Primary Specialist for any file touching engine architecture (scene structure, node hierarchy, lifecycle hooks).
QA Testability Review
For Logic and Integration stories, also spawn qa-tester via Task in parallel with the engine specialists. Pass:
- The implementation files being reviewed
- The story's
## QA Test Casessection (the pre-written test specs from qa-lead) - The story's
## Acceptance Criteria
Ask the qa-tester to evaluate:
- Are all test hooks and interfaces exposed (not hidden behind private/internal access)?
- Do the QA test cases from the story's
## QA Test Casessection map to testable code paths? - Are any acceptance criteria untestable as implemented (e.g., hardcoded values, no seam for injection)?
- Does the implementation introduce any new edge cases not covered by the existing QA test cases?
- Are there any observable side effects that should have a test but don't?
For Visual/Feel and UI stories: qa-tester reviews whether the manual verification steps in ## QA Test Cases are achievable with the implementation as written — e.g., "is the state the manual checker needs to reach actually reachable?"
Collect all specialist findings before producing output.
Phase 8: Output Review
## Code Review: [File/System Name]
### Engine Specialist Findings: [N/A — no engine configured / CLEAN / ISSUES FOUND]
[Findings from engine specialist(s), or "No engine configured." if skipped]
### Testability: [N/A — Visual/Feel or Config story / TESTABLE / GAPS / BLOCKING]
[qa-tester findings: test hooks, coverage gaps, untestable paths, new edge cases]
[If BLOCKING: implementation must expose [X] before tests in ## QA Test Cases can run]
### ADR Compliance: [NO ADRS FOUND / COMPLIANT / DRIFT / VIOLATION]
[List each ADR checked, result, and any deviations with severity]
### Standards Compliance: [X/6 passing]
[List failures with line references]
### Architecture: [CLEAN / MINOR ISSUES / VIOLATIONS FOUND]
[List specific architectural concerns]
### SOLID: [COMPLIANT / ISSUES FOUND]
[List specific violations]
### Game-Specific Concerns
[List game development specific issues]
### Positive Observations
[What is done well -- always include this section]
### Required Changes
[Must-fix items before approval — ARCHITECTURAL VIOLATIONs always appear here]
### Suggestions
[Nice-to-have improvements]
### Verdict: [APPROVED / APPROVED WITH SUGGESTIONS / CHANGES REQUIRED]
This skill is read-only — no files are written.
Phase 9: Next Steps
- If verdict is APPROVED: run
/story-done [story-path]to close the story. - If verdict is CHANGES REQUIRED: fix the issues and re-run
/code-review. - If an ARCHITECTURAL VIOLATION is found: run
/architecture-decisionto record the correct approach.
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 Donchitos/Claude-Code-Game-Studios 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▌
Accelerate Code Development
Use skill to generate boilerplate code, refactor legacy code, and write tests faster
Example
Generate React component with TypeScript types, styled-components, and comprehensive test suite in minutes
Reduce development time by 40-60% for repetitive coding tasks
Code Review Automation
Systematically review code for bugs, security issues, and style violations
Example
Analyze pull requests for common anti-patterns, suggest performance improvements, flag security vulnerabilities
Catch 70%+ of code issues before human review, improve code quality
Debug Complex Issues
Trace errors through stack traces and identify root causes faster
Example
Analyze error logs, suggest probable causes, recommend fixes with code examples
Cut debugging time by 30-50%, especially for unfamiliar codebases
Learn New Technologies
Get explanations, examples, and best practices for unfamiliar frameworks
Example
Understand Next.js app router, learn Rust ownership, grasp Kubernetes concepts with practical examples
Accelerate learning curve by 2-3x, reduce onboarding time for new tech stacks
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill installation support
- ›Basic understanding of programming concepts and version control (Git)
- ›Code editor or IDE for testing generated code (VS Code, JetBrains, etc.)
- ›Test environment separate from production for validating skill outputs
Time Estimate
15-30 minutes to install and see first useful output
Installation Steps
- 1.Install the skill using provided installation command
- 2.Verify skill is loaded in Claude Desktop (check ~/.claude/skills directory)
- 3.Test skill with simple prompt: 'Help me review this code snippet'
- 4.Gradually increase complexity: code generation → refactoring → architecture advice
- 5.Review all generated code before committing to repository
- 6.Iterate on prompts to improve output quality and relevance
- 7.Share effective prompts with team for consistency
Common Pitfalls
- ⚠Blindly trusting generated code without testing—always run tests and manual review
- ⚠Not providing enough context about your project structure and coding standards
- ⚠Expecting perfection on first generation—iteration and refinement are normal
- ⚠Sharing proprietary code or API keys in prompts—maintain confidentiality
- ⚠Over-relying on skill for critical security or business logic code
- ⚠Skipping documentation of why AI-generated code was chosen over alternatives
Best Practices▌
✓ Do
- +Always review and test AI-generated code before merging
- +Provide clear context: language, framework, coding standards, constraints
- +Use for boilerplate, tests, docs—areas where mistakes are easily caught
- +Iterate on prompts: start broad, refine with specific requirements
- +Combine AI suggestions with human judgment and domain expertise
- +Document successful prompt patterns for team reuse
- +Keep version control so you can rollback if needed
- +Use skill for learning and exploration, not production-critical features initially
✗ Don't
- −Don't commit AI code without thorough testing and review
- −Don't expose sensitive code, credentials, or proprietary algorithms
- −Don't use for security-critical code (auth, crypto, payments) without expert review
- −Don't skip peer review process just because AI generated it
- −Don't assume code follows your team's conventions—verify
- −Don't let junior developers skip learning fundamentals by relying solely on AI
- −Don't ignore compiler warnings or test failures in generated code
💡 Pro Tips
- ★Describe desired patterns explicitly: 'Use async/await, avoid callbacks'
- ★Ask for alternatives: 'Show 3 approaches to solve this, with tradeoffs'
- ★Request explanations: 'Explain why this approach is better than X'
- ★Use skill for 70% generation + 30% manual refinement for best results
- ★Build a prompt library for common patterns (API endpoints, components, tests)
- ★Pair program with AI: describe problem → review solution → iterate → refine
When to Use This▌
✓ Use When
Use coding skills for boilerplate generation, code reviews, refactoring legacy code, writing tests, learning new frameworks, and debugging non-critical issues. Best for repetitive tasks where errors are easy to catch.
✗ Avoid When
Avoid for production security features (auth, encryption, payment processing), complex business logic requiring deep domain knowledge, performance-critical algorithms, or when learning fundamentals is more valuable than speed.
Learning Path▌
- 1Start with simple tasks: generate functions, write tests, explain code
- 2Progress to code review: analyze PRs, suggest improvements
- 3Advanced: architectural decisions, refactoring strategies, performance optimization
- 4Expert: use for exploring new paradigms, researching best practices, mentoring juniors
Integration▌
- →VS Code
- →JetBrains IDEs
- →Cursor
- →GitHub Copilot
- →Git workflows
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★72 reviews- ★★★★★Harper Abbas· Dec 28, 2024
Solid pick for teams standardizing on skills: code-review is focused, and the summary matches what you get after install.
- ★★★★★Dev Patel· Dec 28, 2024
Keeps context tight: code-review is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Xiao Jain· Dec 16, 2024
code-review is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Anika Sethi· Dec 8, 2024
code-review is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Ganesh Mohane· Dec 4, 2024
code-review fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Anika Sharma· Nov 27, 2024
code-review reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Harper Srinivasan· Nov 19, 2024
I recommend code-review for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Harper Rahman· Nov 19, 2024
Registry listing for code-review matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Naina Okafor· Nov 7, 2024
code-review reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Amina Zhang· Oct 26, 2024
Registry listing for code-review matched our evaluation — installs cleanly and behaves as described in the markdown.
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