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Prototype

Community
JasonxzWen
prototype

Load when a task needs a throwaway prototype, state-model sanity check, UI variant, image-assisted visual mockup, mock interaction, or playable design; do not use for production feature work.

Overview

PublisherJasonxzWen
Repositoryharness-hub
Skill nameprototype
Stars
71
Forks
0
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by JasonxzWen on GitHub. Read the source before you install it.

Installation

Install the Prototype AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/JasonxzWen/harness-hub.git /tmp/harness-hub
mkdir -p .claude/skills
cp -r /tmp/harness-hub/skills/prototype .claude/skills/prototype
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prototype in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Prototype on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Prototype is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Prototype

Purpose

A prototype is disposable evidence that answers one design question. It should make uncertainty visible before production implementation starts.

Use the smallest evidence that lets the user or agent learn something concrete. Delete it or absorb the validated decision when done.

Pick The Branch

First identify the question.

  • Logic prototype: use when the question is about business rules, data shape, state transitions, command flow, or API feel.
  • UI prototype: use when the question is about layout, interaction, hierarchy, density, or visual alternatives.

If the question is ambiguous, inspect the surrounding code and state the assumption before writing anything.

Read references/logic-prototype.md or references/ui-prototype.md after choosing the branch when implementation details matter.

Rules For Both Branches

  1. Mark every created artifact or code path as throwaway in its name, route, README, top comment, or handoff.
  2. When the evidence is runnable code, keep it near the relevant module, reuse the project's runtime and task runner, and provide one command or URL that starts it.
  3. Avoid persistence unless persistence is the exact question. When it is, use a disposable local file or scratch database whose name makes cleanup obvious.
  4. Skip production polish, broad error handling, and abstractions.
  5. Surface the state, variant, or decision being tested.
  6. Capture the answer in an existing project artifact or the final summary; preserve the prototype itself as durable evidence only when the user explicitly asks.
  7. Delete the prototype or fold the winning decision into production code.

Logic Prototype

Build a tiny interactive terminal app when the question is about behavior.

Keep the reusable logic behind a pure interface:

  • reducer
  • explicit state machine
  • pure functions over plain data
  • small state-owning module with clear methods

The terminal shell is disposable. The reducer, state machine, or function shape can become the real implementation if it survives the prototype.

Show the current state after every action. Keep the UI on one screen when possible.

UI Prototype

Choose the cheapest evidence that can answer the current question: a visual brief for a describable direction, a Host-native image for a static visual question, or runnable UI only when behavior must be experienced. Static images do not verify interaction, responsiveness, or accessibility.

Use Host-native image generation only when a bitmap mockup or reference materially reduces visual uncertainty. Use only public or generated material, or assets the user supplied or explicitly approved for this generation. Reduce private context to de-identified visual descriptors; never send source code, secrets, internal routes, customer or account data, private screenshots, or private copy. Do not add a provider SDK, API key, model adapter, or model-specific runtime to the project. Treat generated images as prototype evidence rather than production UI; if the Host has no native image capability or safe context is unavailable, provide a visual brief and continue without a fallback runtime.

Generate only enough alternatives to distinguish unresolved choices; one direction is enough when validating a single hypothesis. Make each alternative differ in structure or interaction, not just color or copy.

Change only the affected direction while preserving accepted constraints. Reuse the existing page when runnable code needs product context, and add a temporary switcher only when comparing multiple runnable variants in place materially reduces decision cost.

Delete losing alternatives and any comparison control when the question is answered.

Handoff

When handing off, include:

  • the design question
  • how to run or open the prototype
  • what to inspect while using it
  • cleanup expectation

Do not promote prototype code directly to production. Rewrite or harden the chosen path under the normal implementation and verification workflow.

Do not create a branch, commit, push, or publish the prototype unless the user explicitly authorizes that separate delivery action.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Prototype AI skill do?

Load when a task needs a throwaway prototype, state-model sanity check, UI variant, image-assisted visual mockup, mock interaction, or playable design; do not use for production feature work.

Why use Prototype on TypingMind?

Because you install it once and use it with any model. Prototype is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Prototype in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/JasonxzWen/harness-hub/tree/main/skills/prototype. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Prototype?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Prototype?

As many as you like. As long as a model supports skills, you can use Prototype with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Prototype AI skill free?

Yes. It is published on GitHub by JasonxzWen under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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