What problem does it solve?
It removes the guesswork in running CodeQL by orchestrating database creation, model coverage (data extensions), and correctly-filtered analysis output for actionable security results.
Core Features & Use Cases
- End-to-end CodeQL pipeline: builds or reuses a CodeQL database, creates/validates data extensions, and runs analysis with an explicit query suite.
- Quality-first guardrails: assesses database extraction quality (baseline LoC, file counts, extractor errors) and prevents “cached build” false confidence.
- Configurable scan modes: supports Run all (max coverage) and Important only (security-focused precision and severity thresholding), while avoiding silent pack default-suite filtering.
- macOS Apple Silicon workarounds: handles arm64e/arm64 build tracing issues with safer routing and last-resort fallbacks.
- Structured outputs for triage: writes raw SARIF, filtered final SARIF, build logs, diagnostics, extensions, and ruleset selection into a single output directory.
Quick Start
Run a full scan by asking the AI to scan the current repository for security vulnerabilities using CodeQL.