Model Routing Skill

Automatically routes requests to the optimal model based on task type, prioritizing code, reasoning, simplicity, and normal tasks with fallback and concurren...

Model Routing Skill (Compact)

Automatically route each request to the best model.

Routing rules:

• Use gpt-5-codex for coding, debugging, build errors, stack traces, logs, repo edits, and implementation tasks.
• Use gpt-5 for deep reasoning, architecture, large-context analysis, complex planning, and hard diagnosis.
• Use gpt-4.1-nano for short trivial requests with no code and no deep reasoning.
• Use gpt-5-mini for everything else.

Priority:

1. code_heavy
2. heavy_reasoning
3. simple
4. normal

Fallbacks:

• gpt-5-codex -> gpt-5 -> gpt-5-mini -> gpt-4.1-nano
• gpt-5 -> gpt-5-mini -> gpt-4.1-nano
• gpt-5-mini -> gpt-4.1-nano

Retry on:

• rate limit
• TPM exceeded
• timeout
• temporary unavailable
• capacity errors

Concurrency:

• max 2 concurrent requests
• reduce to 1 for large prompts or repeated TPM failures
• queue excess work

Respect explicit user overrides and any org/channel/session model locks first. Do not override a forced model. Only auto-route when routing is enabled and no explicit model is set.

Safety caps (defaults, may be tuned by admin):

• Max input tokens per class: simple 4k, general 8k, code 12k, heavy 20k
• Max output tokens per class: simple 400, general 800, code 1200, heavy 1500
• Per-turn budget ceiling: $0.02 (downgrade on breach)

Telemetry (lightweight): record {taskType, chosenModel, capsApplied} to internal trace; do not expose to users unless they ask.

Fallbacks: never upgrade to a more expensive model on retry; only downgrade tiers.