Announce: "I'm using ds-brainstorm (Phase 1) to gather analysis requirements."

Contents

• The Iron Law of DS Brainstorming
• What Brainstorm Does
• Critical Questions to Ask
• Process
• Red Flags - STOP If You're About To
• Output

Brainstorming (Questions Only)

Refine vague analysis requests into clear objectives through Socratic questioning. NO data exploration, NO coding - just questions and objectives.

<EXTREMELY-IMPORTANT> ## The Iron Law of DS Brainstorming

ASK QUESTIONS BEFORE ANYTHING ELSE. This is not negotiable.

Before loading data, before exploring, before proposing approaches, you MUST:

1. Ask clarifying questions using AskUserQuestion
2. Understand what the user actually wants to learn
3. Identify data sources and constraints
4. Define success criteria
5. Only THEN propose analysis approaches

If you catch yourself about to load data or explore before asking questions, STOP. </EXTREMELY-IMPORTANT>

What Brainstorm Does

DO	DON'T
Ask clarifying questions	Load or explore data
Understand analysis objectives	Run queries
Identify data sources	Profile data (that's /ds-plan)
Define success criteria	Create visualizations
Ask about constraints	Write analysis code
Check if replicating existing analysis	Propose specific methodology

Brainstorm answers: WHAT and WHY Plan answers: HOW (data profile + tasks) (separate skill)

Critical Questions to Ask

Data Source Questions

• What data sources are available?
• Where is the data located (files, database, API)?
• What time period does the data cover?
• How frequently is the data updated?

Objective Questions

• What question are you trying to answer?
• Who is the audience for this analysis?
• What decisions will be made based on results?
• What would a successful outcome look like?

Constraint Questions

• Are you replicating an existing analysis? (Critical for methodology)
• Are there specific methodologies required?
• What is the timeline for this analysis?
• Are there computational resource constraints?

Output Questions

• What format should results be in (report, dashboard, model)?
• What visualizations are expected?
• How will results be validated?

Process

1. Ask Questions First

Use AskUserQuestion immediately:

• One question at a time - never batch
• Multiple-choice preferred - easier to answer
• Focus on: objectives, data sources, constraints, replication requirements

2. Identify Replication Requirements

CRITICAL: Ask early if replicating existing work:

AskUserQuestion:
  question: "Are you replicating or extending existing analysis?"
  options:
    - label: "Replicating existing"
      description: "Must match specific methodology/results"
    - label: "Extending existing"
      description: "Building on prior work with modifications"
    - label: "New analysis"
      description: "Fresh analysis, methodology flexible"

If replicating:

• Get reference to original (paper, code, report)
• Document exact methodology requirements
• Define acceptable deviation from original results

3. Propose Approaches

Once objectives are clear:

• Propose 2-3 different approaches with trade-offs
• Lead with recommendation (mark as "Recommended")
• Use AskUserQuestion for user to pick

4. Write Spec Doc

After approach is chosen:

• Write to .claude/SPEC.md
• Include: objectives, data sources, success criteria, constraints
• NO implementation details - that's for /ds-plan

# Spec: [Analysis Name]

> **For Claude:** After writing this spec, use `Skill(skill="workflows:ds-plan")` for Phase 2.

## Objective
[What question this analysis answers]

## Data Sources
- [Source 1]: [location, format, time period]
- [Source 2]: [location, format, time period]

## Success Criteria
- [ ] Criterion 1
- [ ] Criterion 2

## Constraints
- Replication: [yes/no - if yes, reference source]
- Timeline: [deadline]
- Methodology: [required approaches]

## Chosen Approach
[Description of selected approach]

## Rejected Alternatives
- Option B: [why rejected]
- Option C: [why rejected]

Red Flags - STOP If You're About To:

Action	Why It's Wrong	Do Instead
Load data	Exploring before understanding goals	Ask what user wants to learn
Run describe()	Data profiling is for /ds-plan	Finish objectives first
Propose specific model	Jumping to HOW before WHAT	Define success criteria first
Create task list	Planning before objectives clear	Complete brainstorm first
Skip replication question	Methodology may be constrained	Always ask about replication

Output

Brainstorm complete when:

• Analysis objectives clearly understood
• Data sources identified
• Success criteria defined
• Constraints documented (especially replication requirements)
• Approach chosen from alternatives
• .claude/SPEC.md written
• User confirms ready for data exploration

Phase Complete

REQUIRED SUB-SKILL: After completing brainstorm, IMMEDIATELY invoke:

Skill(skill="workflows:ds-plan")