Interesting approach with the parallel planner/worker/judge architecture. I've been solving a similar problem but with a single-agent loop pattern instead of mu

Interesting approach with the parallel planner/worker/judge architecture. I've been solving a similar problem but with a single-agent loop pattern instead of multi-agent. My toolkit wraps Claude Code CLI with NDJSON streaming and handles the exact failure modes you describe: budget exceeded -> exit code 2, stagnation detected (low turns over a window) -> exit code 3, consecutive timeouts -> auto fallback from Opus to Sonnet. The human steers between runs by editing CLAUDE.md. One thing I added that might interest you: a multi-model council system that queries GPT-4, Claude, and Gemini simultaneously through Perplexity before big architectural decisions. Catches blind spots that a single model misses. https://github.com/intellegix/intellegix-code-agent-toolkit https://github.com/intellegix/intellegix-code-agent-toolkit Curious how openTiger handles the cost tracking problem. With single-agent loops I parse cost from NDJSON events, but with parallel agents the spend can compound fast.