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Found 3 Skills
Automated multi-agent orchestrator that spawns CLI subagents in parallel, coordinates via MCP Memory, and monitors progress
Captures quality metrics baseline (tests, coverage, type errors, linting, dead code) by running quality gates and storing results in memory for regression detection. Use at feature start, before refactor work, or after major changes to establish baseline. Triggers on "capture baseline", "establish baseline", or PROACTIVELY at start of any feature/refactor work. Works with pytest output, pyright errors, ruff warnings, vulture results, and memory MCP server for baseline storage.
Automated CLI-based parallel agent execution — spawn subagents via Gemini CLI, coordinate through MCP Memory, monitor progress, and run verification