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Prototype Ready Spec

Community
Productfculty-aipm
prototype-ready-spec

Use this skill when the user asks to "create a prototype spec", "write a prompt for v0", "write a vibe-coding prompt", "turn this PRD into a prototype prompt", "create a Bolt prompt", "help me prototype this", "write a spec for Lovable", or wants to convert a PRD or feature description into a self-contained prompt that can be dropped directly into v0, Bolt, Lovable, or another AI coding tool. Also auto-invoked at the end of /write-prd to generate the prototype appendix.

Overview

PublisherProductfculty-aipm
RepositoryPM-Copilot-by-Product-Faculty
Skill nameprototype-ready-spec
Stars
80
Forks
34
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Productfculty-aipm on GitHub. Read the source before you install it.

Installation

Install the Prototype Ready Spec 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.
    https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/prototype-ready-spec
  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/Productfculty-aipm/PM-Copilot-by-Product-Faculty.git /tmp/PM-Copilot-by-Product-Faculty
mkdir -p .claude/skills
cp -r /tmp/PM-Copilot-by-Product-Faculty/skills/prototype-ready-spec .claude/skills/prototype-ready-spec
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prototype Ready Spec 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 Ready Spec 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 Ready Spec 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-Ready Spec

You are converting a product spec into a prototype-ready prompt — a self-contained, precise instruction set that can be dropped directly into v0, Bolt, Lovable, or Cursor to generate a working prototype. The goal is to enable a PM to go from PRD to interactive prototype in under 10 minutes.

Framework: Colin Matthews (PRD → prototype in 10 minutes), Aparna Chennapragada (NLX as the new UX — prototyping is now mandatory for PMs).

Key principle from Matthews: "A PM can turn a PRD into a working prototype in under 10 minutes. The spec just needs to be self-contained, scoped to the happy path, and clear about what to exclude." — Lenny's Newsletter (2025)

Step 1 — Load Context

Read memory/user-profile.md for the product context (name, stage, target user). Read the PRD or feature description provided.

Step 2 — Select the Right Tool

Guide the user to the right prototyping tool based on what they need:

NeedBest tool
Quick interactive mockup, no backendv0 (Vercel) — best for React UI components
Full app with simple backendBolt — best for complete application scaffolds
Consumer product, beautiful UILovable — best for polished consumer UX
Complex logic, local iterationCursor — best for local development with AI assist
Conversational / AI feature demoClaude Artifacts — best for chat-based interactions

Ask: "What kind of prototype do you need — a UI flow to show stakeholders, or a working feature to test with users?"

Step 3 — Scope to Happy Path Only

A prototype-ready spec covers ONLY the happy path — the sequence of steps where everything works and the user achieves their goal without errors.

Explicitly exclude from the prototype:

  • Error states and validation
  • Empty states
  • Authentication and authorization flows
  • Admin views
  • Settings and configuration
  • Edge cases
  • Mobile responsiveness (unless that's the prototype's primary purpose)

Step 4 — Write the Prototype Prompt

Generate a self-contained prototype prompt in this structure:

# Prototype: [Feature Name]

## Goal
Build a [happy path only] interactive prototype of [feature name].

## User
[Primary user] — [one sentence: who they are and what they're trying to accomplish in this prototype]

## Core interaction
[One sentence: the single most important thing the user does in this prototype]

## Screens to build

### Screen 1: [Name]
- Purpose: [What this screen achieves]
- Key elements: [List the UI elements — buttons, inputs, cards, etc.]
- User action: [What the user does on this screen]
- Transition: [What happens when they take that action]

### Screen 2: [Name]
- Purpose: [...]
- Key elements: [...]
- User action: [...]
- Transition: [...]

### Screen 3: [Name — usually the success/outcome state]
- Purpose: [What success looks like]
- Key elements: [...]

## Mock data
Use this data in the prototype: [Provide 3–5 realistic example records/items the prototype should display]

## Do NOT build
- Auth flows (start logged in)
- Error states or validation
- Empty states
- Settings or configuration screens
- [Other specific exclusions based on the PRD's out-of-scope section]

## Stack
[React / Next.js / Tailwind CSS — adjust based on tool selected]
No backend required. Use hardcoded mock data.
Focus on interaction flow, not visual polish.

## Definition of done
The prototype is complete when a user can [describe the happy path end-to-end in one sentence] without any blockers.

Step 5 — NLX Design Notes (for AI/conversational features)

If the feature is AI-powered or conversational, add NLX (Natural Language Experience) design notes:

Based on Aparna Chennapragada: "NLX is the new UX — the grammar, structure, and affordances of a natural language conversation are as designable as a visual UI."

  • Conversation grammar: What's the opening message? What are the expected user inputs? What are the response patterns?
  • Invisible UI elements: What does the AI reveal or hide based on context?
  • Natural language affordances: What language cues tell users what they can do next?
  • Fallback behavior: What does the prototype do when the user says something unexpected?

Step 6 — Output

Provide:

  • Tool recommendation with rationale
  • Complete prototype prompt (ready to paste into the tool)
  • NLX design notes (if applicable)
  • Instructions for sharing or testing the prototype

Offer to save the prompt to outputs/prototype-prompt-[feature]-[date].md.

Frequently asked questions

What does the Prototype Ready Spec AI skill do?

Use this skill when the user asks to "create a prototype spec", "write a prompt for v0", "write a vibe-coding prompt", "turn this PRD into a prototype prompt", "create a Bolt prompt", "help me prototype this", "write a spec for Lovable", or wants to convert a PRD or feature description into a self-contained prompt that can be dropped directly into v0, Bolt, Lovable, or another AI coding tool. Also auto-invoked at the end of /write-prd to generate the prototype appendix.

Why use Prototype Ready Spec on TypingMind?

Because you install it once and use it with any model. Prototype Ready Spec 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 Ready Spec in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/prototype-ready-spec. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Prototype Ready Spec?

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 Ready Spec?

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

Is the Prototype Ready Spec AI skill free?

It is published on GitHub by Productfculty-aipm. Check the repository for licensing terms. 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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