super-brainstorm

Convert vague product ideas into validated design specifications with user approval gates.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/Samuelca6399/AbsolutelySkilled --skill super-brainstorm-samuelca6399
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: super-brainstorm
Source: https://github.com/Samuelca6399/AbsolutelySkilled/tree/main/skills/super-brainstorm
Command: npx skills add https://github.com/Samuelca6399/AbsolutelySkilled --skill super-brainstorm-samuelca6399

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

It prevents you from building the wrong thing by forcing an ultrathink, interview-driven planning process that converts vague feature requests into a validated design spec before any implementation starts.

Core Features & Use Cases

  • Plan-mode, interview-first design: Enters plan mode immediately, then runs a structured, dependency-resolved question flow to uncover assumptions, constraints, and edge cases.
  • Deep context and codebase-first intelligence: Performs a mandatory deep context scan and checks the codebase before asking questions, reducing wasted back-and-forth.
  • Spec-first governance and review: Produces a design spec saved to docs/plans and runs a review loop with gated user approval before proceeding to the next step.

Use case example: When you request a new system like “real-time collaboration” and you don’t yet know the right architecture, it will explore options, resolve key decisions, and output an implementation-ready spec.

Quick Start

Use super-brainstorm to plan a new feature by telling the AI what you want to build and asking it to produce a validated design spec before coding.

Frequently Asked Questions about super-brainstorm

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

FAQPage Schema
How do I convert a vague product idea into an implementation-ready design spec?

To convert a vague product idea into a design spec, use an interview-driven planning process that forces deep context discovery and resolves key architectural decisions before coding. This validates scope and minimizes rework by producing an implementation-ready document.

What is the best way to plan architecture for a new feature without knowing the right design?

The best way to plan architecture for a new feature is to perform a codebase-first context scan, then run a structured question flow to explore options and uncover constraints. This resolves unknowns and outputs a reviewed design specification.

How do I gather requirements for a system refactor to prevent misaligned scope?

Gathering requirements for a system refactor requires an ultrathink-based linear interviewing process that uncovers hidden assumptions and edge cases upfront. This enforces plan-mode entry to validate scope before implementation begins.

Can I generate design specs for greenfield projects before writing any code?

Yes, you can generate design specs for greenfield projects before writing code by applying an interview-first planning process. It explores architectural options, resolves key decisions, and saves a reviewed design spec to your docs/plans directory.

How does codebase-first discovery improve the requirements-gathering process?

Codebase-first discovery improves requirements-gathering by performing a mandatory deep context scan of your existing code before asking questions. This reduces wasted back-and-forth by ensuring questions are highly relevant to your current architecture.

When should I not use an interview-driven approach for software design?

You should not use an interview-driven approach for simple component-level decisions that do not require upfront clarity or architectural planning. It is specifically built for complex refactors, new features, and system design discussions needing validated specs.