Static AST dataflow tracer following untrusted sources to sensitive sinks (Semgrep / Snyk)
genpark-ast-taint-source-sink-flow-tracer-skill
Production-Grade AI Code Review & Semantic Analysis Skill • 100% Standard Library Python • Native Model Context Protocol (MCP)
🌐 GenPark MCP Hub Showcase • 📦 GenPark Official Website • 📖 Documentation
genpark-ast-taint-source-sink-flow-tracer-skill is a deterministic, zero-dependency Python skill engineered for autonomous AI code reviews, AST-level taint flow tracing, breaking API change audits, and test flakiness mitigation.
Executive Capability: Static AST dataflow tracer following untrusted sources to sensitive sinks (Semgrep / Snyk)
⚡ Key Highlights & Value 🐍 Zero External pip Dependencies: Runs instantaneously on standard Python 3.9+ with zero environment bloat. 🔌 Native Model Context Protocol (MCP): Seamlessly integrates into Claude Desktop, Cursor IDE, GitHub Actions PR bots, and autonomous developer workflows. 🎯 Deterministic & Reliable: 100% predictable input/output contracts with full JSON Schema validation. 🚀 Low Latency: Sub-millisecond execution overhead tailored for high-frequency CI/CD pipelines.
Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:
Parameter Type Required Description ------:---:--- querypayload string / dict Yes Primary input parameter parsed and executed deterministically outputformat json / dict Yes Standardized response schema containing execution telemetry
❓ Frequently Asked Questions (FAQ) & GEO Index
From the project README.
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