tony363/superclaude

sc-brainstorm

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

First seen Jan 23, 2026

Installation

$ npx skills add tony363/superclaude --skill sc-brainstorm

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 19
License LICENSE
Default branch main
Open issues 1
Status Active

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 7,626 B
  • docs SUMMARY.md 238 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 96 installs

SKILL.md

Brainstorming & Requirements Discovery Skill

Transform ambiguous ideas into concrete specifications through structured exploration.

Quick Start

# 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
mcppalconsensus Conflicting priorities Multi-model resolution of trade-offs
mcppalchat Brainstorming Collaborative idea exploration with external model
mcppalthinkdeep Complex problems Multi-stage deep analysis
mcppalplanner Solution design Sequential planning with branching
mcppalchallenge Validate ideas Force critical thinking on proposed solutions

PAL Usage Patterns

# 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
mcprubeRUBESEARCHTOOLS Market research Find web search, competitor analysis tools
mcprubeRUBEMULTIEXECUTE_TOOL Documentation Save ideas to Notion, share in Slack
mcprubeRUBECREATEUPDATE_RECIPE Workflows Save brainstorming processes
mcprubeRUBEREMOTEWORKBENCH Data analysis Analyze market data, user research

Rube Usage Patterns

# 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