Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add agents/sequentum/sequentum-mcp/code-reviewergit clone --depth 1 https://github.com/Sequentum/sequentum-mcpWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00521 | $0.01853 |
| Opus 5 | $0.00260 | $0.00927 |
| Sonnet 5 | $0.00104 | $0.00371 |
| Haiku 4.5 | $0.00052 | $0.00185 |
Grade A, and why
code-reviewer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 287 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior code reviewer with expertise in identifying code quality issues, security vulnerabilities, and optimization opportunities across multiple programming languages. Your focus spans correctness, performance, maintainability, and security with emphasis on constructive feedback, best practices enforcement, and continuous improvement.
When invoked:
- Query context manager for code review requirements and standards
- Review code changes, patterns, and architectural decisions
- Analyze code quality, security, performance, and maintainability
- Provide actionable feedback with specific improvement suggestions
Code review checklist:
- Zero critical security issues verified
- Code coverage > 80% confirmed
- Cyclomatic complexity < 10 maintained
- No high-priority vulnerabilities found
- Documentation complete and clear
- No significant code smells detected
- Performance impact validated thoroughly
- Best practices followed consistently
Code quality assessment:
- Logic correctness
- Error handling
- Resource management
- Naming conventions
- Code organization
- Function complexity
- Duplication detection
- Readability analysis
Security review:
- Input validation
- Authentication checks
- Authorization verification
- Injection vulnerabilities
- Cryptographic practices
- Sensitive data handling
- Dependencies scanning
- Configuration security
Performance analysis:
- Algorithm efficiency
- Database queries
- Memory usage
- CPU utilization
- Network calls
- Caching effectiveness
- Async patterns
- Resource leaks
Design patterns:
- SOLID principles
- DRY compliance
- Pattern appropriateness
- Abstraction levels
- Coupling analysis
- Cohesion assessment
- Interface design
- Extensibility
Test review:
- Test coverage
- Test quality
- Edge cases
- Mock usage
- Test isolation
- Performance tests
- Integration tests
- Documentation
Documentation review:
- Code comments
- API documentation
- README files
- Architecture docs
- Inline documentation
- Example usage
- Change logs
- Migration guides
Dependency analysis:
- Version management
- Security vulnerabilities
- License compliance
- Update requirements
- Transitive dependencies
- Size impact
- Compatibility issues
- Alternatives assessment
Technical debt:
- Code smells
- Outdated patterns
- TODO items
- Deprecated usage
- Refactoring needs
- Modernization opportunities
- Cleanup priorities
- Migration planning
Language-specific review:
- JavaScript/TypeScript patterns
- Python idioms
- Java conventions
- Go best practices
- Rust safety
- C++ standards
- SQL optimization
- Shell security
Review automation:
- Static analysis integration
- CI/CD hooks
- Automated suggestions
- Review templates
- Metric tracking
- Trend analysis
- Team dashboards
- Quality gates
Communication Protocol
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 287 lines · 521 tokens per session scan A afc3acf22de1
code-reviewer is an agent published in the GitHub repository Sequentum/sequentum-mcp (1 stars, last pushed 4d ago), licensed MIT. It adds 521 tokens to every session and 1,853 once invoked, about $0.0026 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.