What problem does it solve? Regex-based pattern matching misses subtle vulnerabilities like tainted data flowing through multiple function calls or unsafe deserialization behind wrappers. This Skill runs dedicated static analysis tools that understand data flow and language-specific vulnerability patterns, then normalizes their disparate outputs into one actionable report. ## Core Features & Use Cases - Multi-Tool Orchestration: Automatically detects project language from config files (package.json, pyproject.toml, Cargo.toml, go.mod) and runs all applicable analyzers including ESLint, Bandit, Semgrep, Clippy, and govulncheck. - Unified Severity Normalization: Maps every tool's output to a consistent BLOCK/WARN/INFO severity scale so findings are comparable across languages and tools. - Graceful Tool Handling: Skips missing tools with explicit install instructions instead of failing silently, and reports full tool coverage transparency. - Use Case: Before merging an authentication module, run a SAST scan to catch SQL injection via string formatting in Python, unverified JWT usage in TypeScript, and known vulnerable dependencies in Go, all in one consolidated report. ## Quick Start Run a static analysis scan on my changed files and report any security findings by severity.