brainstorming

Generate structured options, a comparison matrix, and a recommendation for a problem.

108|27|Updated Mar 26, 2026

Search Tags:#planning #ideation #discovery #options #decision-making

Ready to run

npx skills add https://github.com/diegosouzapw/omni-skills --skill brainstorming-diegosouzapw

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: brainstorming
Source: https://github.com/diegosouzapw/omni-skills/tree/main/skills/brainstorming
Command: npx skills add https://github.com/diegosouzapw/omni-skills --skill brainstorming-diegosouzapw

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Brainstorming workflow skill helps users who are exploring a problem to structure ideas into distinct options with explicit tradeoffs and a recommended next step.

Core Features & Use Cases

Generate 3-5 genuinely different options, each with a label, summary, and the condition under which it wins.
Produce a decision matrix that compares options on complexity, speed, flexibility, risk, and reversibility.
End with a clear recommendation and the smallest experiment or next step to validate it.

Quick Start

Provide a problem statement and constraints, and have the skill generate 3–5 distinct options with tradeoffs and a recommended path.

Frequently Asked Questions about brainstorming

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I structure brainstorming options with tradeoffs for a complex decision?▼

Generating structured options involves framing constraints, producing 3-5 distinct approaches with explicit tradeoffs, and comparing them on complexity, speed, flexibility, risk, and reversibility. This yields a decision matrix and a final recommendation with an actionable next step.

What is the best way to compare different approaches during problem discovery?▼

Using a decision matrix to compare options on complexity, speed, flexibility, risk, and reversibility provides a structured evaluation. This highlights the specific condition under which each approach wins, leading to a clear recommendation.

How do I generate genuinely different options when exploring a problem?▼

You generate 3-5 genuinely different options by applying framing and constraint capture to your problem statement. Each option receives a label, summary, and the condition under which it wins, ensuring distinct viable approaches rather than minor variations.

Can I use a decision matrix for small projects to validate a recommended path?▼

Yes, a decision matrix works for small projects by ending with a clear recommendation and the smallest experiment to validate it. This ensures that even small-scale problem exploration yields an actionable next step for testing the chosen path.

What constraints do I need to provide for option generation?▼

You need to provide a problem statement and any relevant constraints to start option generation. The process applies these constraints to frame the problem, producing 3-5 distinct options with tradeoffs and a final recommendation for an actionable next step.