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model-selection

Determine which LLM model to use for each agent spawn based on configuration, session directives, and task type

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  • SKILL.md4.9 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Model Selection

Determines which LLM model to use for each agent spawn.

SCOPE

✅ THIS SKILL PRODUCES:

  • A resolved model parameter for every task tool call
  • Persistent model preferences in .squad/config.json
  • Spawn acknowledgments that include the resolved model

❌ THIS SKILL DOES NOT PRODUCE:

  • Code, tests, or documentation
  • Model performance benchmarks
  • Cost reports or billing artifacts

Context

Squad supports 18+ models across three tiers (premium, standard, fast). The coordinator must select the right model for each agent spawn. Users can set persistent preferences that survive across sessions.

5-Layer Model Resolution Hierarchy

Resolution is first-match-wins — the highest layer with a value wins.

LayerNameSourcePersistence
0aPer-Agent Config.squad/config.json → agentModelOverrides.{name}Persistent (survives sessions)
0bGlobal Config.squad/config.json → defaultModelPersistent (survives sessions)
1Session DirectiveUser said "use X" in current sessionSession-only
2Charter PreferenceAgent's charter.md → ## Model sectionPersistent (in charter)
3Task-Aware AutoCode → sonnet, docs → haiku, visual → opusComputed per-spawn
4Defaultclaude-haiku-4.5Hardcoded fallback

Key principle: Layer 0 (persistent config) beats everything. If the user said "always use opus" and it was saved to config.json, every agent gets opus regardless of role or task type. This is intentional — the user explicitly chose quality over cost.

AGENT WORKFLOW

On Session Start

  1. READ .squad/config.json
  2. CHECK for defaultModel field — if present, this is the Layer 0 override for all spawns
  3. CHECK for agentModelOverrides field — if present, these are per-agent Layer 0a overrides
  4. STORE both values in session context for the duration

On Every Agent Spawn

  1. CHECK Layer 0a: Is there an agentModelOverrides.{agentName} in config.json? → Use it.
  2. CHECK Layer 0b: Is there a defaultModel in config.json? → Use it.
  3. CHECK Layer 1: Did the user give a session directive? → Use it.
  4. CHECK Layer 2: Does the agent's charter have a ## Model section? → Use it.
  5. CHECK Layer 3: Determine task type:
    • Code (implementation, tests, refactoring, bug fixes) → claude-sonnet-4.6
    • Prompts, agent designs → claude-sonnet-4.6
    • Visual/design with image analysis → claude-opus-4.6
    • Non-code (docs, planning, triage, changelogs) → claude-haiku-4.5
  6. FALLBACK Layer 4: claude-haiku-4.5
  7. INCLUDE model in spawn acknowledgment: 🔧 {Name} ({resolved_model}) — {task}

When User Sets a Preference

Trigger phrases: "always use X", "use X for everything", "switch to X", "default to X"

  1. VALIDATE the model ID against the catalog (18+ models)
  2. WRITE defaultModel to .squad/config.json (merge, don't overwrite)
  3. ACKNOWLEDGE: ✅ Model preference saved: {model} — all future sessions will use this until changed.

Per-agent trigger: "use X for {agent}"

  1. VALIDATE model ID
  2. WRITE to agentModelOverrides.{agent} in .squad/config.json
  3. ACKNOWLEDGE: ✅ {Agent} will always use {model} — saved to config.

When User Clears a Preference

Trigger phrases: "switch back to automatic", "clear model preference", "use default models"

  1. REMOVE defaultModel from .squad/config.json
  2. ACKNOWLEDGE: ✅ Model preference cleared — returning to automatic selection.

STOP

After resolving the model and including it in the spawn template, this skill is done. Do NOT:

  • Generate model comparison reports
  • Run benchmarks or speed tests
  • Create new config files (only modify existing .squad/config.json)
  • Change the model after spawn (fallback chains handle runtime failures)

Config Schema

.squad/config.json model-related fields:

{
  "version": 1,
  "defaultModel": "claude-opus-4.6",
  "agentModelOverrides": {
    "fenster": "claude-sonnet-4.6",
    "mcmanus": "claude-haiku-4.5"
  }
}
  • defaultModel — applies to ALL agents unless overridden by agentModelOverrides
  • agentModelOverrides — per-agent overrides that take priority over defaultModel
  • Both fields are optional. When absent, Layers 1-4 apply normally.

Fallback Chains

If a model is unavailable (rate limit, plan restriction), retry within the same tier:

Premium:  claude-opus-4.6 → claude-opus-4.6-fast → claude-opus-4.5 → claude-sonnet-4.6
Standard: claude-sonnet-4.6 → gpt-5.4 → claude-sonnet-4.5 → gpt-5.3-codex → claude-sonnet-4
Fast:     claude-haiku-4.5 → gpt-5.1-codex-mini → gpt-4.1 → gpt-5-mini

Never fall UP in tier. A fast task won't land on a premium model via fallback.

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