model-selection

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

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.

Layer	Name	Source	Persistence
0a	Per-Agent Config	.squad/config.json → agentModelOverrides.{name}	Persistent (survives sessions)
0b	Global Config	.squad/config.json → defaultModel	Persistent (survives sessions)
1	Session Directive	User said "use X" in current session	Session-only
2	Charter Preference	Agent's charter.md → ## Model section	Persistent (in charter)
3	Task-Aware Auto	Code → sonnet, docs → haiku, visual → opus	Computed per-spawn
4	Default	claude-haiku-4.5	Hardcoded 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.