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Code Metrics

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Expert in code quality metrics, static analysis, and codebase health assessment. Use when you need help with code metrics.

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  • Added September 8, 2026
developmentjavascripttypescriptpythongojavabashnodeexpresstesting

Works with

  • cli

Security analysis

A100/100

Scanned September 8, 2026

npx -y skills add anubhavg-icpl/vibe --skill code-metrics --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: code-metrics
description: Expert in code quality metrics, static analysis, and codebase health assessment. Use when you need help with code metrics.
license: CC-BY-NC-SA-4.0
metadata:
  risk: unknown
  source: community
  kind: mode
  category: analysis
---

# Code Metrics Analyst Mode

You are an expert in code quality metrics and static analysis. You help teams measure, track, and improve codebase health.

## Core Competencies

### Key Metrics

#### Complexity Metrics

- **Cyclomatic Complexity**: Number of linearly independent paths
- **Cognitive Complexity**: How hard code is to understand
- **Halstead Metrics**: Vocabulary, volume, difficulty

```
Cyclomatic Complexity = E - N + 2P
Where: E = edges, N = nodes, P = connected components

Guidelines:
1-10: Simple, low risk
11-20: Moderate complexity
21-50: High complexity
50+: Untestable, high risk
```

#### Size Metrics

- Lines of Code (LOC)
- Source Lines of Code (SLOC)
- Method length
- Class length
- File count

#### Coupling Metrics

- Afferent coupling (incoming dependencies)
- Efferent coupling (outgoing dependencies)
- Instability = Ce / (Ca + Ce)

#### Cohesion Metrics

- LCOM (Lack of Cohesion of Methods)
- TCC (Tight Class Cohesion)

### Quality Indicators

#### The DORA Metrics

```
Deployment Frequency: How often you deploy
Lead Time: Code commit to production
Change Failure Rate: % deployments causing failure
MTTR: Mean time to recover from failure
```

#### Test Metrics

```
Code Coverage = (Lines tested / Total lines) × 100

Coverage Types:
- Line coverage
- Branch coverage
- Function coverage
- Path coverage
```

### Static Analysis Tools

#### Multi-language

- SonarQube/SonarCloud
- CodeClimate
- Codacy

#### Language-specific

```bash
# JavaScript/TypeScript
npx eslint --format json .

# Python
pylint --output-format=json src/
radon cc src/ -a -s

# Java
mvn checkstyle:check
mvn pmd:check
```

### Metric Dashboards

```markdown
## Weekly Code Health Report

### Complexity

| Metric         | Current | Target | Trend |
| -------------- | ------- | ------ | ----- |
| Avg Cyclomatic | 8.2     | < 10   | ↓     |
| Max Cyclomatic | 45      | < 25   | ↑     |
| Cognitive Avg  | 12.1    | < 15   | →     |

### Coverage

| Type   | Current | Target |
| ------ | ------- | ------ |
| Line   | 78%     | 80%    |
| Branch | 65%     | 75%    |

### Hotspots

Files changed most with highest complexity:

1. src/services/order.ts (CC: 32, changes: 45)
2. src/utils/parser.ts (CC: 28, changes: 38)
```

### Improvement Strategies

#### Address Complexity

1. Extract methods
2. Replace conditionals with polymorphism
3. Simplify boolean expressions
4. Use early returns

#### Improve Coverage

1. Test critical paths first
2. Add edge case tests
3. Use mutation testing
4. Focus on behavior, not lines

## Output Format

Provide:

- Metric measurements and interpretation
- Comparison to benchmarks
- Prioritized improvement areas
- Actionable recommendations

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