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model-tiers.md

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1# Model Tiers
2
3Read this when dispatching a sub-agent (the Phase 1.1 grounding scout, the Phase 2.6 claim verifier, or the opt-in Slack researcher). Sub-agent dispatch is tiered by task shape, never hardcoded to a model name:
4
5- **Extraction tier** — the grounding scout: retrieval and quoting work. Use the platform's cheapest capable model when the current harness exposes a known override. "Capable" is part of the spec — escalate to the generation tier when the repo is large or the stack obscure.
6- **Generation tier** — the claim verifier: evidence-driven mechanical verification. Use the platform's mid-tier model when the current harness exposes a known override. If model names are unknown, omit the override and inherit rather than guessing.
7- **Ceiling tier** — the dialogue itself. Questions, approaches, synthesis, and the requirements-only unified plan run in the main conversation on the orchestrator's model; nothing is dispatched for them.
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9If the user's or project's active instructions or the live prompt name a model for this subagent, use that model instead of the default tier above. They can name it by the subagent's tier, by its prompt-asset name, or for the subagents being dispatched. Without such an instruction, a model configured for this subagent's role takes precedence over the default tier.
11**Degradation rule.** When the platform's subagent primitive does not support per-agent model selection, dispatch the scout and verifier on the inherited model and keep their read budgets and output caps — cost control then comes from structure, not tiering. When the platform has no subagent primitive at all, do the topic scan inline at Phase 1.1 — still writing the grounding dossier to the scratch path, because downstream consumers (the Phase 2.6 verifier, the ce-plan handoff) receive that path — and verify claims inline before the Phase 3 write, with the same budgets.
13Classify a rejected native dispatch by whether an agent launched: correct a pre-launch argument rejection once, leave capacity-limited work queued, and send any other failure to the inline degradation above.

Model Tiers

Read this when dispatching a sub-agent (the Phase 1.1 grounding scout, the Phase 2.6 claim verifier, or the opt-in Slack researcher). Sub-agent dispatch is tiered by task shape, never hardcoded to a model name:

  • Extraction tier — the grounding scout: retrieval and quoting work. Use the platform's cheapest capable model when the current harness exposes a known override. "Capable" is part of the spec — escalate to the generation tier when the repo is large or the stack obscure.
  • Generation tier — the claim verifier: evidence-driven mechanical verification. Use the platform's mid-tier model when the current harness exposes a known override. If model names are unknown, omit the override and inherit rather than guessing.
  • Ceiling tier — the dialogue itself. Questions, approaches, synthesis, and the requirements-only unified plan run in the main conversation on the orchestrator's model; nothing is dispatched for them.

If the user's or project's active instructions or the live prompt name a model for this subagent, use that model instead of the default tier above. They can name it by the subagent's tier, by its prompt-asset name, or for the subagents being dispatched. Without such an instruction, a model configured for this subagent's role takes precedence over the default tier.

Degradation rule. When the platform's subagent primitive does not support per-agent model selection, dispatch the scout and verifier on the inherited model and keep their read budgets and output caps — cost control then comes from structure, not tiering. When the platform has no subagent primitive at all, do the topic scan inline at Phase 1.1 — still writing the grounding dossier to the scratch path, because downstream consumers (the Phase 2.6 verifier, the ce-plan handoff) receive that path — and verify claims inline before the Phase 3 write, with the same budgets.

Classify a rejected native dispatch by whether an agent launched: correct a pre-launch argument rejection once, leave capacity-limited work queued, and send any other failure to the inline degradation above.

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