How do I install the AI Brainstorm skill?

Run npx skillmds add majiayu000/ai-brainstorm in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is AI Brainstorm safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with AI Brainstorm?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is AI Brainstorm free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published AI Brainstorm?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

AI Brainstorm by majiayu000 — Agent Skill

Name: AI Brainstorm
Rating: 4.2 (5 reviews)
Author: majiayu000

File contents

Brainstorm

Purpose

Design interrogation skill. Forces rigorous thinking BEFORE any code is written. Produces an approved spec that becomes the contract for /ai-plan.

HARD GATE: this skill produces a spec. No implementation happens until the user explicitly approves it.

When to Use

User says "I want to build...", "how should we...", "let's design..."
New feature, architecture change, or ambiguous requirement
Any work where jumping straight to code would be premature

Process

Load context -- read specs/spec.md, decision-store.json, and docs/solution-intent.md section 7 (roadmap)
- If a work item ID is provided (e.g., AB#100 or #45): a. Read .ai-engineering/manifest.yml work_items section for active provider and team config b. Fetch work item and its hierarchy from the provider:
  - GitHub: gh issue view <number> --json title,body,labels,milestone,assignees
  - Azure DevOps: az boards work-item show --id <number> --expand relations -o json c. Walk the hierarchy: Feature → User Story → Tasks (follow parent/child relations) d. Use all standard and custom fields the platform provides e. Pre-fill refs section in the generated spec frontmatter
Interrogate -- follow handlers/interrogate.md for the questioning flow
Propose approaches -- present 2-3 options with trade-offs (never just one)
Draft spec -- write spec to specs/spec.md
Review spec -- follow handlers/spec-review.md for the review loop (max 3 iterations)
STOP -- present approved spec. User runs /ai-plan to continue.

Quick Reference

Step	Gate	Output
Interrogate	All UNKNOWNs resolved	Requirements map
Propose	User selects approach	Chosen design
Spec draft	Written to disk	spec.md
Spec review	Subagent approves	Reviewed spec
User approval	User says "approved"	HARD GATE passed

Questioning Rules

ONE question at a time. Never batch.
Prefer multiple choice (A/B/C) over open-ended.
Challenge vague language: "improve", "optimize", "clean up" are not requirements.
Push back on scope creep. Ask: "Is this in scope for v1?"
Explore edge cases the user has not mentioned.
Max 10 questions per session. If you need more, the problem is too big -- split it.

Common Mistakes

Skipping interrogation and jumping to the spec.
Proposing only one approach (always propose 2-3).
Writing implementation details in the spec (specs describe WHAT, not HOW).
Not challenging the user's assumptions.
Producing a spec without the review loop.

Integration

Called by: user directly, or /ai-plan when requirements are unclear
Calls: handlers/interrogate.md, handlers/spec-review.md
Transitions to: /ai-plan (ONLY -- never directly to ai-build or /ai-dispatch)

$ARGUMENTS

---name: ai-brainstormdescription: Use when the user wants to design, architect, or explore a feature before building it. HARD GATE: no implementation until the user approves the spec.--- # Brainstorm ## Purpose Design interrogation skill. Forces rigorous thinking BEFORE any code is written. Produces an approved spec that becomes the contract for `/ai-plan`. HARD GATE: this skill produces a spec. No implementation happens until the user explicitly approves it. ## When to Use - User says "I want to build...", "how should we...", "let's design..." - New feature, architecture change, or ambiguous requirement - Any work where jumping straight to code would be premature ## Process 1. **Load context** -- read `specs/spec.md`, `decision-store.json`, and `docs/solution-intent.md` section 7 (roadmap) - If a work item ID is provided (e.g., `AB#100` or `#45`): a. Read `.ai-engineering/manifest.yml` `work_items` section for active provider and team config b. Fetch work item and its hierarchy from the provider: - **GitHub**: `gh issue view <number> --json title,body,labels,milestone,assignees` - **Azure DevOps**: `az boards work-item show --id <number> --expand relations -o json` c. Walk the hierarchy: Feature → User Story → Tasks (follow parent/child relations) d. Use all standard and custom fields the platform provides e. Pre-fill `refs` section in the generated spec frontmatter 2. **Interrogate** -- follow `handlers/interrogate.md` for the questioning flow 3. **Propose approaches** -- present 2-3 options with trade-offs (never just one) 4. **Draft spec** -- write spec to `specs/spec.md` 5. **Review spec** -- follow `handlers/spec-review.md` for the review loop (max 3 iterations) 6. **STOP** -- present approved spec. User runs `/ai-plan` to continue. ## Quick Reference | Step | Gate | Output | |------|------|--------| | Interrogate | All UNKNOWNs resolved | Requirements map | | Propose | User selects approach | Chosen design | | Spec draft | Written to disk | spec.md | | Spec review | Subagent approves | Reviewed spec | | User approval | User says "approved" | HARD GATE passed | ## Questioning Rules - ONE question at a time. Never batch. - Prefer multiple choice (A/B/C) over open-ended. - Challenge vague language: "improve", "optimize", "clean up" are not requirements. - Push back on scope creep. Ask: "Is this in scope for v1?" - Explore edge cases the user has not mentioned. - Max 10 questions per session. If you need more, the problem is too big -- split it. ## Common Mistakes - Skipping interrogation and jumping to the spec. - Proposing only one approach (always propose 2-3). - Writing implementation details in the spec (specs describe WHAT, not HOW). - Not challenging the user's assumptions. - Producing a spec without the review loop. ## Integration - **Called by**: user directly, or `/ai-plan` when requirements are unclear - **Calls**: `handlers/interrogate.md`, `handlers/spec-review.md` - **Transitions to**: `/ai-plan` (ONLY -- never directly to `ai-build` or `/ai-dispatch`) $ARGUMENTS

Frequently asked questions