Multi-Model Consultation

Query advisory subagents (GPT, Gemini, Grok) based on user request. Spawn ONLY the models explicitly mentioned.

Available Models

Trigger Patterns - MATCH EXACTLY

Parse user request and spawn ONLY requested models:

Default behavior: If ambiguous, ask user which model(s) they want. Do NOT default to all three.

Workflow

Step 1: Identify Requested Models

Parse user request carefully:

• •Single model mentioned → spawn only that one
• •Two models mentioned → spawn only those two
• •"all three" / "all models" → spawn all three
• •Ambiguous → ask for clarification

Step 2: Form Your Own Opinion First

Before spawning subagents:

• •What's your initial assessment?
• •What are the key considerations?
• •What's your preliminary recommendation?

Step 3: Spawn Requested Models in Parallel

Spawn ONLY the models user requested, all at once:

# Single model example
Task 1: @gpt - [the question]

# Two models example  
Task 1: @gpt - [the question]
Task 2: @gemini - [the question]

# All three example
Task 1: @gpt - [the question]
Task 2: @gemini - [the question]
Task 3: @grok - [the question]

Step 4: Synthesize Responses

Adapt synthesis to number of models:

Single model:

## My Analysis
[Your assessment]

## [Model]'s Perspective
[Summary of response]

## Synthesis
[Compare your view with model's, final recommendation]

Two models:

## My Analysis
[Your assessment]

## [Model 1]'s Perspective
[Summary]

## [Model 2]'s Perspective
[Summary]

## Synthesis
### Agreement
[Where perspectives align]

### Divergence
[Where they differ]

### Recommendation
[Final recommendation with rationale]

Three models:

## My Analysis
[Your assessment]

## GPT's Perspective
[Summary]

## Gemini's Perspective
[Summary]

## Grok's Perspective
[Summary]

## Synthesis
### Agreement
[Where all align]

### Divergence
[Where they differ and why]

### Recommendation
[Final recommendation, which arguments most compelling]

Decision Framework

When Models Agree

• •High confidence in shared conclusion
• •Note if reasoning differs despite same answer

When Models Disagree

• •Identify root cause (assumptions? priorities? training data?)
• •Evaluate which reasoning fits THIS context
• •Your role: break tie with reasoned judgment

When You Disagree

• •State your position clearly
• •Explain why their reasoning doesn't apply
• •Be open to being wrong

NEVER

• •NEVER spawn models not requested - respect user's choice
• •NEVER default to all three when user asks for one or two
• •NEVER spawn sequentially - always parallel
• •NEVER skip forming your own opinion first
• •NEVER just average answers - synthesize with judgment
• •NEVER hide disagreement - surface it explicitly

Examples

Single model: User: "ask gpt about early bird vs night owl" → Spawn @gpt only, synthesize with your view

Two models: User: "ask gpt and gemini about monorepo vs polyrepo" → Spawn @gpt + @gemini only, synthesize both with your view

All three: User: "ask all three about best testing strategy" → Spawn @gpt + @gemini + @grok, full synthesis