aedelon/brainstorm

Multi-Agent Brainstorm

Overview

Structured brainstorming that combines clarifying dialogue with parallel expert sub-agents. The goal: understand the problem first, then get diverse expert perspectives, then synthesize.

Process

Phase 1: CLARIFY   → Understand the topic (2-3 targeted questions)
Phase 2: MAP       → Select relevant expert agents
Phase 3: EXPLORE   → Spawn agents in parallel
Phase 4: SYNTHESIZE → Combine and present findings

Phase 1: Clarify the Topic

Before spawning any agent, understand what the user actually needs.

Ask 2-3 targeted questions (one at a time, prefer multiple choice):

• What is the core problem or goal?
• What constraints exist? (tech stack, budget, timeline, existing code)
• What does success look like?

Rules:

• One question per message
• Prefer multiple choice via AskUserQuestion when possible
• Max 3 questions — don't interrogate, get enough context to spawn useful agents
• If the topic is already clear and specific, skip to Phase 2

Phase 2: Map to Expert Agents

Select 2-4 relevant agents from this mapping:

| Domain | Agent Type | |--------|------------| | AI/ML Research | research-synthesizer | | Creative / Image Gen | midjourney-expert | | Finance/Crypto/Tax | finance-advisor | | Prompt Engineering | prompt-engineer | | Architecture/Design | feature-dev:code-architect | | Code Review | feature-dev:code-reviewer | | General research | general-purpose |

Selection criteria:

• Pick agents that bring different perspectives on the topic
• At least one agent should challenge the obvious approach
• For cross-domain topics, pick agents from different domains

Phase 3: Explore via Parallel Agents

Spawn all selected agents simultaneously using the Agent tool.

Each agent prompt MUST include:

Brainstorm: [topic with context from Phase 1]

Context: [key constraints and goals identified]

Your task:
1. Propose 2-3 approaches from your domain expertise
2. For each approach: trade-offs, risks, and when it works best
3. Justify every recommendation with sources (docs, papers, experience)
4. State confidence level (HIGH/MEDIUM/LOW) for each claim
5. Flag anything you cannot verify
6. Highlight what you'd do differently from the obvious approach

Important:

• Use model: "opus" for complex/architectural topics
• Use model: "sonnet" for straightforward domain questions
• All agents run in parallel — never sequential

Phase 4: Synthesize

After all agents return, present a unified synthesis:

## Synthesis: [Topic]

### Consensus
[What multiple agents agree on — strongest signal]

### Divergent Views
[Where agents disagree, with rationale from each side]

### Recommended Approach
[Best path forward, justified by agent findings]
[State which agent perspectives informed this recommendation]

### Trade-offs to Consider
[Key decisions the user still needs to make]

### Sources
[All sources cited by agents, deduplicated]

### Confidence: [LEVEL]
[Based on source agreement and verification quality]

Edge Cases

Topic too vague

Ask one clarifying question. If still vague after 2 questions, brainstorm at the level of abstraction given.

No obvious agent match

Use general-purpose agents with specific domain prompts. Always spawn at least 2.

User wants to go deeper

After synthesis, offer to spawn additional agents on specific sub-topics that emerged.

Quick brainstorm

If user says "quick" or the topic is narrow, skip Phase 1 and spawn 2 agents directly.