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prototype

Create throwaway prototypes for state-machine logic, UI variations, or data-model decisions.

Updated May 11, 2026
Search Tags:#design#prototype#in-memory#state-machine#rapid-feedback#ui-variation#throwaway
One-click install
npx skills add https://github.com/cloudofgeorge/AI-hands --skill prototype-cloudofgeorge
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prototype
Source: https://github.com/cloudofgeorge/AI-hands/tree/main/skills/engineering/prototype
Command: npx skills add https://github.com/cloudofgeorge/AI-hands --skill prototype-cloudofgeorge

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Throwaway prototypes help teams flesh out a design before committing to it, enabling fast exploration of approaches.

Core Features & Use Cases

  • Supports branching between UI and logic prototypes.
  • Provides a near-codebase-local prototype that can be started with a single command.
  • Useful for evaluating design options and data-model decisions.

Quick Start

Run the project's existing task runner with the prototype command to start exploring the chosen design branch.

Frequently Asked Questions about prototype

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

FAQPage Schema
How do I create a throwaway prototype to validate a UI design before committing to the codebase?▼

A throwaway prototype validates UI design by living close to the feature code, running with a single command, and avoiding persistence by default. This enables fast exploration of design approaches before committing to the final implementation.

What is the best way to prototype state-machine logic without setting up a full database?▼

Prototyping state-machine logic in-memory avoids persistence by default, allowing rapid feedback on branching logic. This approach helps flesh out data-model decisions and state transitions without the overhead of a permanent database setup.

Can I run a prototype locally with a single command to test data-model decisions?▼

Yes, the prototype must be runnable in a single command using the project's existing task runner. This near-codebase-local execution model lets you quickly evaluate data-model decisions and UI variations without complex setup procedures.

When should I use throwaway prototypes instead of building features directly in the main codebase?▼

Use throwaway prototypes when exploring state-machine logic, UI variations, or data-model decisions before commitment. They provide rapid feedback on design options without the risk of polluting your main codebase with experimental branches or temporary persistence layers.

Does prototyping in-memory work for evaluating branching between UI and logic prototypes?▼

In-memory prototyping supports branching between UI and logic prototypes effectively. By avoiding persistence by default, it allows teams to flesh out design approaches and rapidly iterate on both interface variations and underlying logic structures.

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