gemma4:e2b has native function calling with dedicated tool tokens,
achieving 100% tool selection accuracy in benchmarks vs 67% for
mistral-nemo-large, with 5-8x faster response times (2-4s vs 15-20s)
and lower VRAM usage (8GB vs 9.2GB).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
- Rewrite system prompt with negative constraints and step-by-step process
- Set temperature to 0.1 for deterministic tool calling
- Sort room groups to top of device list (address positional bias)
- Add [ROOM GROUP] marker in list_devices output
- Update tool docstrings with explicit entity_id= parameter examples
- Add optimization findings doc (experiment log: 0% → 100% success)
- Add test script for room group detection regression testing
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>