agent-contracts Routing Tuning

Use this skill when you are designing or debugging routing behavior (rule matches vs LLM selection).

Routing Model (what to optimize)

1. Rule filtering via TriggerCondition (when / when_not, priority)
2. Candidate selection (top matches + ties)
3. Optional LLM decision among candidates (with llm_hint)
4. Fallbacks and terminal states (response.response_type)

Practical Tuning Steps

1. Make rule-based selection deterministic first (LLM off).
2. Use priorities to express business rules (100+ = critical, 50-99 = main, 1-49 = fallback).
3. Add llm_hint only where ambiguity remains after rules.
4. Use context_builder only when needed; keep default minimal slices.
5. Debug with decidewithtrace() and inspect matched rules.

Guardrails

• Prefer rules for safety/constraints; use LLM for ambiguous intent.
• Keep candidate sets small and explainable.
• Treat response.response_type terminal values as part of routing design.

References (load only when needed)

• docs/core_concepts.md (Traceable Routing / Context Builder)
• examples/02routingexplain.py
• docs/skills/official/agent-contracts-routing-tuning/references/debug_playbook.md