ReddRadar
Agent skill
code-quality-analyzer
Static code analysis, technical debt assessment, engineering velocity metrics
Install this agent skill to your Project
npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/business/venture-capital/skills/code-quality-analyzer
Metadata
Additional technical details for this skill
- domain
- business
- skill id
- vc-skill-014
- specialization
- venture-capital
SKILL.md
Code Quality Analyzer
Overview
The Code Quality Analyzer skill provides detailed code-level analysis for technical due diligence. It performs static code analysis, assesses technical debt, and evaluates engineering team velocity to understand code health and development productivity.
Capabilities
Static Code Analysis
- Run automated code quality checks
- Identify code smells and anti-patterns
- Measure code complexity metrics
- Detect potential bugs and vulnerabilities
Technical Debt Assessment
- Quantify technical debt backlog
- Identify high-priority refactoring needs
- Assess test coverage and quality
- Evaluate documentation completeness
Engineering Velocity Metrics
- Measure deployment frequency
- Track lead time for changes
- Analyze cycle time and throughput
- Assess sprint velocity trends
Code Health Indicators
- Analyze code churn patterns
- Review pull request metrics
- Assess code review practices
- Evaluate dependency management
Usage
Analyze Code Quality
Input: Repository access, analysis parameters
Process: Run static analysis, aggregate metrics
Output: Code quality report, issue summary
Assess Technical Debt
Input: Codebase access, debt categorization
Process: Inventory debt, estimate remediation
Output: Technical debt assessment, prioritization
Measure Engineering Velocity
Input: Git history, project management data
Process: Calculate velocity metrics
Output: Velocity report, trend analysis
Review Code Health
Input: Repository data, team practices
Process: Analyze patterns, compare benchmarks
Output: Code health scorecard, recommendations
Key Metrics
| Metric | Description | Target Range |
|---|---|---|
| Test Coverage | % of code covered by tests | 70-90% |
| Code Complexity | Cyclomatic complexity average | < 10 |
| Tech Debt Ratio | Debt remediation time / dev time | < 5% |
| Deployment Frequency | Deployments per week | Daily to weekly |
| Change Failure Rate | % of deployments causing issues | < 15% |
Integration Points
- Technical Due Diligence: Detailed code analysis for DD
- Tech Stack Scanner: Complement architecture review
- Technical Assessor (Agent): Support agent analysis
- IP Patent Analyzer: Code-level IP assessment
Analysis Tools Integration
- SonarQube for code quality
- CodeClimate for maintainability
- GitHub/GitLab analytics
- Jira/Linear for velocity data
- Custom scripts for specific checks
Best Practices
- Calibrate expectations by company stage
- Focus on trends over absolute numbers
- Consider context of rapid iteration
- Balance debt against velocity needs
- Assess relative to team size and resources
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