name: code-health description: Analyze codebase health - large files, test coverage gaps, duplicate code, dead/legacy code, and documentation issues. Use when asked to scan, audit, or assess code quality, find refactoring targets, or identify technical debt.

Code Health Analysis

Run scripts/health.py to analyze codebase health. The script auto-detects project type (Go, Python, JS/TS) and runs appropriate checks.

Usage

Primary (LLM/programmatic use):

# Full scan with JSON output (recommended for LLM consumption)
python /path/to/skill/scripts/health.py --json [directory]

# Specific checks with JSON output
python /path/to/skill/scripts/health.py --check size --json [directory]
python /path/to/skill/scripts/health.py --check tests --json [directory]
python /path/to/skill/scripts/health.py --check dupes --json [directory]
python /path/to/skill/scripts/health.py --check dead --json [directory]
python /path/to/skill/scripts/health.py --check docs --json [directory]

Secondary (human debugging):

# Human-readable output with emojis (for manual inspection)
python /path/to/skill/scripts/health.py [directory]
python /path/to/skill/scripts/health.py --check size [directory]

Checks

Output

JSON format (recommended): Structured output for LLM/programmatic parsing with severity levels:

• "critical": Immediate attention needed
• "warning": Should address soon
• "info": Nice to fix

Each finding includes file path, line number (when applicable), message, and suggested action.

Human-readable format (debugging only): Pretty-printed output with emoji severity indicators (🔴 critical, 🟡 warning, 🟢 info) for manual inspection.

AST-Based Function Analysis

For more accurate function analysis, use the included AST parsers:

gofuncs - Go Function Analyzer

go run scripts/gofuncs.go -dir /path/to/project

Output format: file:line:type:exported:name:receiver:signature

• type: f=function, m=method
• exported: y=public, n=private

Example:

api.go:15:f:n:fetchItems:()[]Item
config.go:144:m:y:GetCategory:*Mapper:(string)string

pyfuncs - Python Function Analyzer

python scripts/pyfuncs.py --dir /path/to/project

Output format: file:line:type:exported:name:class:signature:decorators

• type: f=function, m=method, s=staticmethod, c=classmethod, p=property
• exported: y=public, n=private (underscore prefix)

Example:

main.py:15:f:y:process_data::(data:List[str])->Dict[str,int]:
api.py:45:m:y:fetch:APIClient:async (url:str)->Response:cache,retry

jsfuncs - JavaScript/TypeScript Function Analyzer

node scripts/jsfuncs.js --dir /path/to/project

Output format: file:line:type:exported:name:class:signature:decorators

• type: f=function, m=method, a=arrow, c=constructor, g=getter, s=setter
• exported: y=public, n=private

Example:

main.js:15:f:y:processData::(data:string[])=>Promise<Object>:
api.ts:45:m:y:fetch:APIClient:async (url:string)=>Response:

Use Cases for AST Tools

These tools provide accurate function-level analysis for:

• Complexity analysis: Count functions per file, analyze parameter complexity
• Test coverage: Identify which specific functions lack tests
• Duplicate detection: Find similar function signatures across the codebase
• API surface analysis: List all public vs private functions
• Documentation gaps: Cross-reference with doc comments

Combine with health.py for comprehensive codebase health analysis.

Requirements

Required: python3 Optional (for better results): rg (ripgrep), fd, git, go (for Go projects), staticcheck, node (for JS/TS projects)

Missing tools are reported but don't block execution.