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Prototype

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ProgrammerAnthony
prototype

快速验证设计的一次性原型。区分两条分支——逻辑/状态模型用终端交互 App,UI 布局用多变体路由切换。当用户想原型验证、检验数据模型或状态机、探索多种 UI 方案时触发。触发词:原型、prototype、验证方案、快速试验、让我玩一玩、试几个设计。

Overview

PublisherProgrammerAnthony
RepositoryExpert-Coding-Harness
Skill nameprototype
Stars
236
Forks
77
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 ProgrammerAnthony 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/ProgrammerAnthony/Expert-Coding-Harness.git /tmp/Expert-Coding-Harness
mkdir -p .claude/skills
cp -r /tmp/Expert-Coding-Harness/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.

原型(Prototype)

原型是回答一个问题的一次性代码。问题决定形态,答完即删。

选分支

根据用户提示、周边代码、或直接询问来判断问题属于哪类:

  • "这段逻辑/状态模型的设计感觉对吗?"references/LOGIC.md。构建一个微型终端交互 App,手动驱动状态机穿越难以凭空推理的边界 Case。
  • "这个界面应该长什么样?"references/UI.md。在单个路由上生成几个差异显著的 UI 变体,通过浮动底栏切换。

分支错误会浪费整个原型。若问题确实模糊且用户不在线,则默认按周边代码选择(后端模块→逻辑;页面/组件→UI),并在原型顶部声明该假设。

两条分支通用规则

  1. 从第一天起就是一次性代码,且明确标记。 将原型代码放在它实际服务的模块或页面旁边,名称中包含 prototype 以示一次性身份。
  2. 一条命令即可运行。 使用项目现有任务管理器(pnpm <name>python <path> 等),用户不需要记路径。
  3. 默认不持久化。 状态存内存。若问题本身涉及数据库,使用临时 DB 或带有 "PROTOTYPE — wipe me" 标记的本地文件。
  4. 跳过打磨。 不写测试、不做错误处理(仅保留让原型能运行的最低限度)、不做抽象。目标是快速学到东西然后删掉它。
  5. 暴露状态。 每次操作后(逻辑)或每次切换变体后(UI),打印或渲染完整的相关状态。
  6. 完成后删除或吸收。 原型回答完问题后,要么删除,要么将经过验证的决策折叠进真实代码——不要让它在仓库里腐烂。

完成时

原型唯一值得保留的是答案。将其记录在某个持久化位置(commit message、ADR、issue,或原型旁边的 NOTES.md),连同它所回答的问题一并保存。若用户在场,几句对话即可;若不在,留好占位符供后续填写,然后删除原型。

详细指南

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?

快速验证设计的一次性原型。区分两条分支——逻辑/状态模型用终端交互 App,UI 布局用多变体路由切换。当用户想原型验证、检验数据模型或状态机、探索多种 UI 方案时触发。触发词:原型、prototype、验证方案、快速试验、让我玩一玩、试几个设计。

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/ProgrammerAnthony/Expert-Coding-Harness/tree/master/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 ProgrammerAnthony 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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