---
name: sc-brainstorm
description: Interactive requirements discovery through Socratic dialogue and systematic exploration. Use when transforming ambiguous ideas into concrete specifications, validating concepts, or coordinating multi-persona analysis.
---

# Brainstorming & Requirements Discovery Skill

Transform ambiguous ideas into concrete specifications through structured exploration.

## Quick Start

```bash
# Basic brainstorm
/sc:brainstorm [topic]

# Deep systematic exploration
/sc:brainstorm "AI project management tool" --strategy systematic --depth deep

# Parallel exploration with multiple personas
/sc:brainstorm "real-time collaboration" --strategy agile --parallel
```

## Behavioral Flow

1. **Explore** - Transform ambiguous ideas through Socratic dialogue
2. **Analyze** - Coordinate multiple personas for domain expertise
3. **Validate** - Apply feasibility assessment across domains
4. **Specify** - Generate concrete specifications
5. **Handoff** - Create actionable briefs for implementation

## Flags

| Flag | Type | Default | Description |
|------|------|---------|-------------|
| `--strategy` | string | systematic | systematic, agile, enterprise |
| `--depth` | string | normal | shallow, normal, deep |
| `--parallel` | bool | false | Enable parallel exploration paths |
| `--validate` | bool | false | Include feasibility validation |

## Personas Activated

- **architect** - System design and technical feasibility
- **analyzer** - Requirements analysis and complexity assessment
- **frontend** - User experience and interface considerations
- **backend** - API and data architecture
- **security** - Security requirements and compliance
- **devops** - Infrastructure and deployment considerations
- **project-manager** - Timeline and resource planning

## MCP Integration

### PAL MCP (Collaborative Intelligence)

| Tool | When to Use | Purpose |
|------|-------------|---------|
| `mcp__pal__consensus` | Conflicting priorities | Multi-model resolution of trade-offs |
| `mcp__pal__chat` | Brainstorming | Collaborative idea exploration with external model |
| `mcp__pal__thinkdeep` | Complex problems | Multi-stage deep analysis |
| `mcp__pal__planner` | Solution design | Sequential planning with branching |
| `mcp__pal__challenge` | Validate ideas | Force critical thinking on proposed solutions |

### PAL Usage Patterns

```bash
# Consensus on conflicting priorities
mcp__pal__consensus(
    models=[
        {"model": "gpt-5.2", "stance": "for", "stance_prompt": "Prioritize user experience"},
        {"model": "gemini-3-pro", "stance": "against", "stance_prompt": "Prioritize technical simplicity"},
        {"model": "deepseek", "stance": "neutral"}
    ],
    step="Evaluate: Should we use real-time sync or eventual consistency?"
)

# Deep exploration of complex idea
mcp__pal__thinkdeep(
    step="Exploring AI-powered analytics dashboard concept",
    hypothesis="Users need predictive insights, not just historical data",
    confidence="medium",
    focus_areas=["user_needs", "technical_feasibility", "market_fit"]
)

# Collaborative brainstorming
mcp__pal__chat(
    prompt="Help me explore innovative approaches for real-time collaboration in document editing",
    model="gpt-5.2",
    thinking_mode="high"
)

# Challenge assumptions
mcp__pal__challenge(
    prompt="We assume users want AI-generated summaries. Is this assumption valid?"
)

# Plan solution architecture
mcp__pal__planner(
    step="Planning architecture for real-time notification system",
    step_number=1,
    total_steps=4,
    is_branch_point=True,
    branch_id="websocket-approach"
)
```

### Rube MCP (Research & Persistence)

| Tool | When to Use | Purpose |
|------|-------------|---------|
| `mcp__rube__RUBE_SEARCH_TOOLS` | Market research | Find web search, competitor analysis tools |
| `mcp__rube__RUBE_MULTI_EXECUTE_TOOL` | Documentation | Save ideas to Notion, share in Slack |
| `mcp__rube__RUBE_CREATE_UPDATE_RECIPE` | Workflows | Save brainstorming processes |
| `mcp__rube__RUBE_REMOTE_WORKBENCH` | Data analysis | Analyze market data, user research |

### Rube Usage Patterns

```bash
# Research market and competitors
mcp__rube__RUBE_SEARCH_TOOLS(queries=[
    {"use_case": "web search", "known_fields": "query:AI analytics dashboard competitors 2025"}
])

# Document brainstorming session
mcp__rube__RUBE_MULTI_EXECUTE_TOOL(tools=[
    {"tool_slug": "NOTION_CREATE_PAGE", "arguments": {
        "title": "Brainstorm: AI Analytics Dashboard",
        "content": "## Key Ideas\n- Predictive insights\n- Natural language queries\n\n## Decisions\n- Real-time sync chosen over eventual consistency"
    }},
    {"tool_slug": "SLACK_SEND_MESSAGE", "arguments": {
        "channel": "#product",
        "text": "New brainstorm session documented: AI Analytics Dashboard"
    }}
])

# Create user research tasks
mcp__rube__RUBE_MULTI_EXECUTE_TOOL(tools=[
    {"tool_slug": "JIRA_CREATE_ISSUE", "arguments": {
        "project": "PROD",
        "summary": "User research: AI analytics preferences",
        "issue_type": "Task",
        "description": "Interview 10 users about analytics needs"
    }},
    {"tool_slug": "ASANA_CREATE_TASK", "arguments": {
        "name": "Competitor analysis: analytics dashboards",
        "project": "Research"
    }}
])

# Analyze existing user feedback
mcp__rube__RUBE_REMOTE_WORKBENCH(
    thought="Analyze user feedback data for patterns",
    code_to_execute='''
import json
# Load user feedback from file
feedback_data = json.load(open("/tmp/user_feedback.json"))
# Analyze with LLM
analysis, error = invoke_llm(f"Analyze this user feedback for analytics feature requests: {feedback_data[:5000]}")
output = {"analysis": analysis, "feedback_count": len(feedback_data)}
output
'''
)
```

## Flags (Extended)

| Flag | Type | Default | Description |
|------|------|---------|-------------|
| `--pal-consensus` | bool | false | Use PAL consensus for trade-offs |
| `--pal-deep` | bool | false | Use PAL thinkdeep for complex exploration |
| `--research` | bool | false | Use Rube for market/competitor research |
| `--document` | string | - | Document to Rube (notion, confluence, google-docs) |
| `--notify` | string | - | Notify via Rube (slack, teams, email) |

## Evidence Requirements

This skill does NOT require hard evidence. Focus on:
- Documenting exploration paths and decisions
- Recording stakeholder input and priorities
- Capturing specifications and requirements

## Exploration Strategies

### Systematic (`--strategy systematic`)
- Structured question-driven discovery
- Comprehensive domain coverage
- Documentation-heavy approach

### Agile (`--strategy agile`)
- Rapid iteration cycles
- User story focused
- Minimal viable specification

### Enterprise (`--strategy enterprise`)
- Compliance and governance focus
- Stakeholder alignment
- Risk assessment integration

## Examples

### Product Discovery
```
/sc:brainstorm "AI-powered analytics dashboard" --strategy systematic --depth deep
# Multi-persona analysis with comprehensive feasibility
```

### Feature Exploration
```
/sc:brainstorm "real-time notifications" --strategy agile --parallel
# Parallel paths: frontend UX, backend architecture, security implications
```

### Enterprise Solution
```
/sc:brainstorm "enterprise data platform" --strategy enterprise --validate
# Compliance-aware exploration with security and devops input
```

## Tool Coordination

- **Read/Write** - Requirements documentation
- **TodoWrite** - Exploration progress tracking
- **Task** - Parallel exploration delegation
- **WebSearch** - Market research and technology validation