An AI Development Control Layer — sits between the developer and the LLM, turning vague requests into controlled, risk-assessed engineering plans.
v0.1-experiment: research seed. One command, fully tested offline pipeline.
py -m governor.cli plan <repo-path> "<change request>"
Runs four stages: ingest (repo scan) → analyze (risk) → decompose (subtasks) → promptgen (constrained prompts). Writes plan.json.
Use --kimi with KIMI_API_KEY set for real LLM analysis (default is an offline mock for development/testing).
py -m pytest tests -v # 11 tests, no API key needed
Implements the controlled workflow from: O. Hanan, "Controlled AI-Assisted Development in Student Software Projects" (AIFE 2026).