Enables orchestrating multi-agent AI coding workflows with Git worktree isolation, parallel testing, and security scanning via the Model Context Protocol.
Enables AI coding agents to diagnose and repair Python Selenium UI automation using real evidence from live DOM and test runs, with enforced safety boundaries and verifiable fixes.
Enables AI coding agents to debug Python projects by running pytest, extracting failure locations, displaying code context around failures, and optionally requesting fix suggestions from Gemini.
Enables reproducible evaluation of AI coding agents by exposing repository inspection, code editing, test running, and deterministic verification through MCP tools.
Enables deterministic evaluation of coding agents by exposing controlled repository tools and returning structured verification reports with pattern checks and repeat-run comparisons.