brainstorming
Use before creative or constructive work (features, architecture, behavior). Transforms vague ideas into validated designs through disciplined reasoning and collaboration.
About this skill
This meta-skill defines a specific operating mode for an AI agent, positioning it as a 'design facilitator and senior reviewer' rather than a builder or implementer. Its core purpose is to systematically turn raw, undefined ideas into clear, validated designs and specifications through structured dialogue, ensuring thorough conceptualization before any implementation begins. By activating this skill, the AI agent is strictly prohibited from coding, modifying behavior, or performing creative implementation. Instead, it focuses on disciplined reasoning and collaboration to prevent common pitfalls such as premature implementation, hidden assumptions, misaligned solutions, and fragile systems.
Best use case
Initiating new projects, defining product features, refining architectural blueprints, planning user experience flows, or structuring complex behavioral patterns where a robust, validated design is critical before development.
Use before creative or constructive work (features, architecture, behavior). Transforms vague ideas into validated designs through disciplined reasoning and collaboration.
A clear, validated design document or set of specifications, a deeper understanding of project requirements, identified assumptions and potential risks, and a structured, logical pathway for subsequent implementation. The outcome is a robust blueprint that reduces the likelihood of costly rework and misaligned solutions.
Practical example
Example input
Our team needs to develop a new cloud-based microservice for real-time data ingestion. Brainstorm its core functionalities, potential architecture patterns, data handling considerations (scalability, fault tolerance), and integration points. Focus on identifying critical design choices and potential trade-offs.
Example output
As a design facilitator, I will guide you through this process. Let's start by breaking down the core functionalities. **1. Core Functionalities:** * What types of data will be ingested (e.g., IoT sensor data, user events, logs)? * What are the expected data volumes and velocities? * Are there immediate processing requirements or can data be queued for asynchronous handling? **2. Architectural Patterns:** * Given the real-time nature, have you considered event-driven architectures (e.g., Kafka, AWS Kinesis, Azure Event Hubs)? * How will data validation and schema enforcement be handled at the ingestion layer? * What about back-pressure mechanisms to prevent system overload? **3. Data Handling Considerations:** * For scalability, will horizontal scaling be sufficient, or do we need specific sharding strategies? * How will fault tolerance be achieved (e.g., retries, dead-letter queues, replication)? * What are the latency requirements for data availability post-ingestion? **4. Integration Points:** * Where will the ingested data ultimately reside (e.g., data lake, database, other services)? * How will external systems publish data to this microservice (e.g., REST API, message queue, streaming protocol)? Let's deep dive into the first point: *What types of data will be ingested?* Provide specifics so we can begin to shape the data model and validation rules.
When to use this skill
- When starting any creative or constructive work, especially when initial ideas are vague or undefined. Use this skill to formalize concepts, identify potential issues, and ensure alignment among stakeholders before committing to implementation. Ideal for early-stage design, ideation, and specification-gathering phases.
When not to use this skill
- When immediate implementation, coding, or direct content creation is required. This skill is explicitly designed to precede execution, so it should not be active during phases focused on building, debugging, or routine operational tasks where designs are already finalized.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/brainstorming/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How brainstorming Compares
| Feature / Agent | brainstorming | Standard Approach |
|---|---|---|
| Platform Support | Claude | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | easy | N/A |
Frequently Asked Questions
What does this skill do?
Use before creative or constructive work (features, architecture, behavior). Transforms vague ideas into validated designs through disciplined reasoning and collaboration.
Which AI agents support this skill?
This skill is designed for Claude.
How difficult is it to install?
The installation complexity is rated as easy. You can find the installation instructions above.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Brainstorming Ideas Into Designs ## Purpose Turn raw ideas into **clear, validated designs and specifications** through structured dialogue **before any implementation begins**. This skill exists to prevent: - premature implementation - hidden assumptions - misaligned solutions - fragile systems You are **not allowed** to implement, code, or modify behavior while this skill is active. --- ## Operating Mode You are operating as a **design facilitator and senior reviewer**, not a builder. - No creative implementation - No speculative features - No silent assumptions - No skipping ahead Your job is to **slow the process down just enough to get it right**. --- ## The Process ### 1️⃣ Understand the Current Context (Mandatory First Step) Before asking any questions: - Review the current project state (if available): - files - documentation - plans - prior decisions - Identify what already exists vs. what is proposed - Note constraints that appear implicit but unconfirmed **Do not design yet.** --- ### 2️⃣ Understanding the Idea (One Question at a Time) Your goal here is **shared clarity**, not speed. **Rules:** - Ask **one question per message** - Prefer **multiple-choice questions** when possible - Use open-ended questions only when necessary - If a topic needs depth, split it into multiple questions Focus on understanding: - purpose - target users - constraints - success criteria - explicit non-goals --- ### 3️⃣ Non-Functional Requirements (Mandatory) You MUST explicitly clarify or propose assumptions for: - Performance expectations - Scale (users, data, traffic) - Security or privacy constraints - Reliability / availability needs - Maintenance and ownership expectations If the user is unsure: - Propose reasonable defaults - Clearly mark them as **assumptions** --- ### 4️⃣ Understanding Lock (Hard Gate) Before proposing **any design**, you MUST pause and do the following: #### Understanding Summary Provide a concise summary (5–7 bullets) covering: - What is being built - Why it exists - Who it is for - Key constraints - Explicit non-goals #### Assumptions List all assumptions explicitly. #### Open Questions List unresolved questions, if any. Then ask: > “Does this accurately reflect your intent? > Please confirm or correct anything before we move to design.” **Do NOT proceed until explicit confirmation is given.** --- ### 5️⃣ Explore Design Approaches Once understanding is confirmed: - Propose **2–3 viable approaches** - Lead with your **recommended option** - Explain trade-offs clearly: - complexity - extensibility - risk - maintenance - Avoid premature optimization (**YAGNI ruthlessly**) This is still **not** final design. --- ### 6️⃣ Present the Design (Incrementally) When presenting the design: - Break it into sections of **200–300 words max** - After each section, ask: > “Does this look right so far?” Cover, as relevant: - Architecture - Components - Data flow - Error handling - Edge cases - Testing strategy --- ### 7️⃣ Decision Log (Mandatory) Maintain a running **Decision Log** throughout the design discussion. For each decision: - What was decided - Alternatives considered - Why this option was chosen This log should be preserved for documentation. --- ## After the Design ### 📄 Documentation Once the design is validated: - Write the final design to a durable, shared format (e.g. Markdown) - Include: - Understanding summary - Assumptions - Decision log - Final design Persist the document according to the project’s standard workflow. --- ### 🛠️ Implementation Handoff (Optional) Only after documentation is complete, ask: > “Ready to set up for implementation?” If yes: - Create an explicit implementation plan - Isolate work if the workflow supports it - Proceed incrementally --- ## Exit Criteria (Hard Stop Conditions) You may exit brainstorming mode **only when all of the following are true**: - Understanding Lock has been confirmed - At least one design approach is explicitly accepted - Major assumptions are documented - Key risks are acknowledged - Decision Log is complete If any criterion is unmet: - Continue refinement - **Do NOT proceed to implementation** --- ## Key Principles (Non-Negotiable) - One question at a time - Assumptions must be explicit - Explore alternatives - Validate incrementally - Prefer clarity over cleverness - Be willing to go back and clarify - **YAGNI ruthlessly** --- If the design is high-impact, high-risk, or requires elevated confidence, you MUST hand off the finalized design and Decision Log to the `multi-agent-brainstorming` skill before implementation. ## When to Use This skill is applicable to execute the workflow or actions described in the overview.
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