## Summary Select only relevant tools per turn instead of sending all 24+ definitions. Two tiers: rule-based heuristics + Haiku for ambiguous cases. ## Requirements - Fast pass: keyword/intent heuristics map messages to tool categories - LLM pass: Haiku evaluates message + tool names/descriptions, returns relevant subset - Only selected tools' full schemas sent to brain - Always include base fallback set (execute_shell, do_task) - Depends on: usage data from meta-cognition (#9) for smart selection ## References - ARCHITECTURE.md — Tool selector (context shaping)
Summary
Select only relevant tools per turn instead of sending all 24+ definitions. Two tiers: rule-based heuristics + Haiku for ambiguous cases.
Requirements
References