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Prd V04 Visual Prototype Gate

Community
mattgierhart
prd-v04-visual-prototype-gate

Generate visual prototype prompts from SCR- entries for Google Stitch (or equivalent UI generation tool). Triggers on: 'make a prototype', 'visualize screens', 'generate Stitch prompt', 'I need a visual demo', 'prototype the workflow', 'show me what this looks like', 'get this to a demo', 'visual gate'. Consumes SCR- (Screen Flow Definition), PER- (Personas), UJ- (User Journeys), DES- (Design Components). Outputs Stitch prompt blocks per SCR- entry + Feedback Capture Template. No new SoT IDs created — this skill makes existing SCR- entries visual and routes feedback back to them.

Overview

Publishermattgierhart
RepositoryPRD-driven-context-engineering
Skill nameprd-v04-visual-prototype-gate
Stars
179
Forks
11
Bundled files
3
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Prd V04 Visual Prototype Gate 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/mattgierhart/PRD-driven-context-engineering.git /tmp/PRD-driven-context-engineering
mkdir -p .claude/skills
cp -r /tmp/PRD-driven-context-engineering/plugins/prd-ce/skills/prd-v04-visual-prototype-gate .claude/skills/prd-v04-visual-prototype-gate
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prd V04 Visual Prototype Gate 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 Prd V04 Visual Prototype Gate 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 Prd V04 Visual Prototype Gate 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.

Visual Prototype Gate

Position in workflow: v0.4 Screen Flow Definition → v0.4 Visual Prototype Gate → v0.5 Red Team Review

Screens on paper are hypotheses. Screens rendered visually are testable. This skill converts SCR- entries into structured prompts for Google Stitch (or any UI generation tool), then captures feedback routed back to specific SoT IDs.

Rule: No product advances past v0.4 without a visual prototype reviewed by at least one stakeholder.

Consumes

  • SCR-* entries (from Screen Flow Definition) — Each SCR- becomes one Stitch prompt. 1:1 mapping, no exceptions.
  • PER-* entries (from Persona Definition) — User context shapes copy, complexity, and emotional framing per screen.
  • UJ-* entries (from User Journey Mapping) — Journey position determines each screen's emotional beat (uncertainty → clarity → confidence).
  • DES-* entries (from Screen Flow Definition) — Shared components referenced in prompts for visual consistency.
  • BR-* business rules — Constraints affecting visual layout (pricing tiers, role-based visibility, data rules).

Produces

  • Stitch Prompt Block per SCR- — One structured prompt per screen, ready to paste into Stitch. Grouped by UJ- journey for context.
  • Prototype Context Brief — Product context + design style preamble (pasted once into Stitch before screen prompts).
  • Feedback Capture Template — Table mapping each prototype screen to its SCR- ID for structured review. See assets/feedback-capture-template.md.
  • No new SoT IDs — This skill visualizes existing IDs. Feedback routes back to SCR-, DES-, or CFD- entries.

Step-by-Step Process

Step 1: Confirm Inputs Exist

Check that Screen Flow Definition is complete:

  • At least 3 SCR- entries exist with Purpose, Key Elements, and Related IDs populated
  • At least 1 UJ- journey references those screens
  • Design style preference confirmed with user (or default: "Clean B2B SaaS, minimal, professional")

If SCR- entries are incomplete, stop and run prd-v04-screen-flow-definition first.

Step 2: Write the Prototype Context Brief

One block, written once per product. This is pasted into Stitch as the opening context before individual screen prompts.

PRODUCT CONTEXT
[2-3 sentences from PRD v0.1 Spark: what the product is, who uses it, what pain it solves]

PRIMARY USER
[From PER-001: role, context, technical comfort level]

DESIGN STYLE
[Confirmed aesthetic — e.g., "Clean B2B SaaS, dark sidebar, minimal. Color for status only."]

Step 3: Generate Per-Screen Prompts

For each SCR- entry, produce one Stitch prompt block. Follow this template:

SCREEN: [SCR-XXX] — [Screen Name]
Journey position: [UJ-XXX], Step [N] of [Total]
User goal: [From SCR- Purpose field]
Situation: [What just happened — derived from prior UJ- step]
Key UI elements: [From SCR- Key Elements, using specific UI/UX keywords]
  - [Element 1: be specific — "green 'Run' button, top right, disabled until selection made"]
  - [Element 2: reference DES-XXX if shared component]
  - [Element 3+]
Constraints: [BR-XXX rules affecting this screen — e.g., "free tier sees max 3 items"]
Emotional beat: [Derived from journey position — early=uncertainty, mid=engagement, end=confidence]
Layout: [UI surface type — full page, sidebar panel, modal, card grid, etc.]

Stitch-specific guidance (from research):

  • Use UI/UX keywords: "navigation bar," "card layout," "call-to-action," not vague terms like "a button"
  • One screen per Stitch generation for best results — do not combine multiple SCR- entries into one prompt
  • Include adjectives for aesthetic: "minimal," "clean," "dark," "warm" — Stitch uses these for palette and typography
  • Reference specific positions: "top-right," "below the header," "spanning full width"

Step 4: Identify the Money Shot

Select the single screen that communicates core product value fastest. This is typically the screen at the UJ- "Moment of Value" step. Mark it in the output. This frame gets screenshotted for any stakeholder deck, landing page, or pitch.

Step 5: Output Feedback Capture Template

Alongside prompts, output the feedback capture template (see assets/feedback-capture-template.md). This is the structured review artifact — reviewers annotate per-screen, feedback routes to specific IDs.

Stitch Workflow Notes

Google Stitch iterates best with incremental refinement:

  1. Paste the Prototype Context Brief first
  2. Generate one screen at a time using per-screen prompts
  3. Refine each screen with targeted follow-ups ("Move the CTA to the right," "Change card layout to 2-column grid")
  4. Export to Figma if design iteration continues beyond prototype stage

For non-Stitch tools, see references/tool-adaptation-notes.md.

Quality Gates (v0.4 → v0.5 Readiness)

Before proceeding to v0.5 Red Team Review:

  • All SCR- entries have a corresponding visual prototype screen
  • At least one stakeholder has reviewed the prototype
  • Feedback Capture Template is completed with disposition for each item
  • Money Shot identified and captured

Downstream Connections

ConsumerWhat It Uses
v0.5 Red Team ReviewVisual prototype informs risk assessment — "does this feel buildable?"
v0.6 ArchitectureValidated screens inform API data requirements
v0.7 Build ExecutionPrototype becomes the visual spec for implementation
Stakeholder CommunicationMoney Shot used in decks, pitches, landing pages

Detailed References

  • Feedback capture template: See assets/feedback-capture-template.md
  • Tool adaptation notes: See references/tool-adaptation-notes.md
  • Screen count guidelines: See references/screen-count-guidelines.md

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 Prd V04 Visual Prototype Gate AI skill do?

Generate visual prototype prompts from SCR- entries for Google Stitch (or equivalent UI generation tool). Triggers on: 'make a prototype', 'visualize screens', 'generate Stitch prompt', 'I need a visual demo', 'prototype the workflow', 'show me what this looks like', 'get this to a demo', 'visual gate'. Consumes SCR- (Screen Flow Definition), PER- (Personas), UJ- (User Journeys), DES- (Design Components). Outputs Stitch prompt blocks per SCR- entry + Feedback Capture Template. No new SoT IDs created — this skill makes existing SCR- entries visual and routes feedback back to them.

Why use Prd V04 Visual Prototype Gate on TypingMind?

Because you install it once and use it with any model. Prd V04 Visual Prototype Gate 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 Prd V04 Visual Prototype Gate in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/mattgierhart/PRD-driven-context-engineering/tree/main/plugins/prd-ce/skills/prd-v04-visual-prototype-gate. 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 Prd V04 Visual Prototype Gate?

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 Prd V04 Visual Prototype Gate?

As many as you like. As long as a model supports skills, you can use Prd V04 Visual Prototype Gate with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Prd V04 Visual Prototype Gate AI skill free?

Yes. It is published on GitHub by mattgierhart 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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