library/specializations/code-migration-modernization/skills/static-code-analyzer/SKILL.md
Deep static analysis of codebases for quality, complexity, and migration readiness assessment
npx skillsauth add a5c-ai/babysitter static-code-analyzerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Performs comprehensive static analysis of codebases to assess code quality, complexity metrics, and migration readiness. This skill integrates with industry-standard tools to provide actionable insights for migration planning.
Enable deep static analysis of codebases for:
This skill can leverage the following external tools when available:
| Tool | Purpose | Integration Method | |------|---------|-------------------| | SonarQube | Comprehensive code quality | MCP Server / API | | CodeClimate | Quality metrics | API | | ESLint | JavaScript/TypeScript linting | CLI | | PMD | Java static analysis | CLI | | FindBugs/SpotBugs | Java bug detection | CLI | | Checkstyle | Java code standards | CLI | | ast-grep | AST-based pattern matching | MCP Server / CLI | | Semgrep | Security-focused SAST | CLI |
# Invoke skill for basic analysis
# The skill will auto-detect language and apply appropriate analyzers
# Expected inputs:
# - targetPath: Path to codebase or directory to analyze
# - analysisScope: 'full' | 'quick' | 'security' | 'quality'
# - outputFormat: 'json' | 'markdown' | 'html'
Discovery Phase
Tool Selection
Analysis Execution
Report Generation
{
"analysisId": "string",
"timestamp": "ISO8601",
"target": {
"path": "string",
"languages": ["string"],
"filesAnalyzed": "number",
"linesOfCode": "number"
},
"metrics": {
"complexity": {
"average": "number",
"max": "number",
"distribution": {}
},
"duplication": {
"percentage": "number",
"cloneCount": "number",
"duplicatedLines": "number"
},
"maintainability": {
"index": "number",
"grade": "A-F"
},
"technicalDebt": {
"estimatedHours": "number",
"ratio": "number"
}
},
"findings": [
{
"type": "string",
"severity": "critical|high|medium|low|info",
"file": "string",
"line": "number",
"message": "string",
"rule": "string",
"recommendation": "string"
}
],
"migrationReadiness": {
"score": "number (0-100)",
"blockers": [],
"risks": [],
"recommendations": []
}
}
This skill integrates with the following Code Migration/Modernization processes:
Create .static-analyzer.json in the project root:
{
"excludePaths": ["node_modules", "dist", "build", ".git"],
"severityThreshold": "medium",
"enabledChecks": {
"complexity": true,
"duplication": true,
"security": true,
"standards": true
},
"customRules": [],
"reportFormats": ["json", "markdown"]
}
When SonarQube MCP Server is available:
// Example MCP tool invocation
{
"tool": "sonarqube_analyze",
"arguments": {
"project_key": "my-project",
"sources": "./src",
"language": "javascript"
}
}
When ast-grep MCP Server is available:
// Example AST pattern search
{
"tool": "ast_grep_search",
"arguments": {
"pattern": "console.log($$$)",
"language": "javascript",
"path": "./src"
}
}
code-smell-detector: Specialized smell detectiontechnical-debt-quantifier: Debt measurement and prioritizationtest-coverage-analyzer: Coverage gap identificationlegacy-system-archaeologist: Uses this skill for codebase explorationmigration-readiness-assessor: Uses this skill for readiness scoringtechnical-debt-auditor: Uses this skill for debt assessmentdevelopment
Model documentation skill for generating model cards following Google's model card framework.
development
MLflow integration skill for experiment tracking, model registry, and artifact management. Enables LLMs to log experiments, compare runs, manage model lifecycle, and retrieve artifacts through the MLflow API.
data-ai
LIME-based local explanation skill for individual predictions across tabular, text, and image data.
devops
Kubeflow Pipelines skill for ML workflow orchestration, component management, and Kubernetes-native ML.