[intellegix]

This separation of planning and execution is exactly the pattern I ended up building into an open source toolkit for Claude Code. The key insight that made autonomous loops work was giving the loop driver awareness of the CLAUDE.md file as the "plan" layer — the human edits CLAUDE.md between runs to steer the project, and the loop driver handles execution (session continuity, budget enforcement, stagnation detection, model fallback from Opus to Sonnet on consecutive timeouts).

The other piece that helped was a multi-model council system — before committing to a major architectural decision, the toolkit queries GPT-4, Claude, and Gemini simultaneously through Perplexity, then synthesizes with Opus. Having three models surface their assumptions (as the top comment here describes) catches more blind spots than any single model.

194 pytest tests, MIT licensed: https://github.com/intellegix/intellegix-code-agent-toolkit