Production LLM Router Spec (PRD + Checklist)

Goal
Build a routing layer that makes multi-model LLM features predictable, auditable, and cost-controlled. The router is responsible for model selection, policy enforcement, validation, and traceability.

Scope (what the router must own)
1) Request classification
- Detect: sensitivity (PII/regulatory), workflow risk (read vs write actions), output format requirements (free text vs JSON), latency class (interactive vs batch).
- Store classification result as a first-class field on the trace.

2) Routing policy
- Route based on: sensitivity, required modality, required structured output, customer deployment constraints (region/data retention), user tier, and cost ceilings.
- Define explicit fallbacks per route (don’t rely on implicit retries).

3) Output constraints + validation
- Support JSON schema validation for structured outputs.
- Enforce tool permissions: allowlist tools per route; validate tool arguments; cap tool-call depth.
- Define refusal behavior for blocked content and for policy violations.

4) Observability + audit
Capture per request:
- Provider, model identifier, and parameters (temperature/top_p/tool mode).
- Prompt template ID and a redacted rendered prompt.
- Retrieval context references (doc IDs/chunk hashes) and embedding/search parameters.
- Tool calls and tool outputs (status codes, latency, errors).
- Policy gate results (PII detected, jailbreak signals, allow/deny decision).
- Cost attribution fields (per-tenant, per-route) and caching decisions.

5) Evals + regression
- Maintain a small eval set per route (golden prompts + expected properties).
- On model changes: run evals automatically; block rollout on failures.
- Track failures by route and model version (not just “overall quality”).

Rollout plan (operator-friendly)
1) Start with one high-risk workflow (sensitive data or write actions).
2) Implement “deny by default” tool permissions; require explicit allows.
3) Add schema validation if any downstream code depends on structure.
4) Add fallbacks: timeout -> alternate model; schema fail -> stricter prompt -> human review queue.
5) Turn on trace logging, then do an incident rehearsal: pick a bad output and verify you can reconstruct why it happened.

Go-live checklist
- [ ] Each route has an explicit owner and an eval set.
- [ ] Logs are accessible to engineering + security (with redaction).
- [ ] Data retention and region behavior are documented per provider/deployment.
- [ ] Hard caps exist for context size and tool-call depth.
- [ ] Fallback behavior is deterministic and tested.
- [ ] A kill switch exists per route and per provider.

Definition of Done
Operators can answer: what happened, why it happened, what it cost, and how to prevent it—using the router’s artifacts, not guesswork.