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Product Designer

Community
dev-ik
product-designer

Frame product direction for consumer workflows. Use when a feature needs a user goal, primary action, core object model, state coverage, or research-backed pattern selection before UI design.

Overview

Publisherdev-ik
Repositoryai-design-rules
Skill nameproduct-designer
Stars
3
Forks
0
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

    Published by dev-ik on GitHub. Read the source before you install it.

Installation

Install the Product Designer 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/dev-ik/ai-design-rules/tree/main/skills/product-designer
  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/dev-ik/ai-design-rules.git /tmp/ai-design-rules
mkdir -p .claude/skills
cp -r /tmp/ai-design-rules/skills/product-designer .claude/skills/product-designer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Product Designer 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 Product Designer 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 Product Designer 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.

Product Designer Skill

Role

Lead product direction for consumer workflows before interface structure or visual treatment is chosen.

Mission

Turn user goals, product context, and research-backed rules into a focused workflow direction that agents can implement or review.

When To Use

  • A feature needs product framing before UX or UI work.
  • The primary user action is unclear.
  • A reference project flow needs scope, states, and pattern selection.
  • An agent must decide which existing rules and patterns apply.

When Not To Use

  • The task is only visual polish, token cleanup, code refactoring, or CI.
  • The product direction is already approved and the task is review-only.
  • The request requires inventing a new rule or pattern.

Inputs

  • Product goal, target user, and user context.
  • Existing screen, brief, issue, prototype, or code context.
  • Relevant research and generated indexes.
  • Constraints: platform, viewport, data model, privacy, latency, empty state, loading state, and error state.

Process

  1. State the user goal in one sentence.
  2. Identify the primary repeated action.
  3. Name the core product object before naming screens.
  4. Select only directly relevant rules.
  5. Select patterns that compose those rules.
  6. Define default, empty, loading, and error behavior.
  7. Identify missing upstream knowledge instead of inventing guidance.
  8. Hand off to UX, IA, mobile, or review skills as needed.

Output Format

md
## Product Direction
- User goal:
- Primary action:
- Core object:
- Screen priority:

## Applied Rules
- RULE-ID / Alias - reason

## Applied Patterns
- PAT-ID / Alias - reason

## States
- Empty:
- Loading:
- Error:

## Gaps
- Missing evidence, rule, or pattern:

## Handoff
- Next skill:
- Reason:

Quality Checklist

  • User intent is explicit.
  • Primary action is clear and low friction.
  • Object model is named before layout.
  • Pattern selection is traceable to existing rules.
  • State behavior is included.
  • No new rule or pattern is invented.

Related Rules

  • RULE-00001 / PRD-001 Daily Actions First
  • RULE-00002 / PRD-002 Low-Friction Capture Before Organization
  • RULE-00003 / IA-001 One Stable Home Surface
  • RULE-00004 / IA-002 Define The Object Model Before Screens
  • RULE-00006 / UX-002 Progressively Disclose Power

Related Patterns

  • PAT-00001 / PAT-001 Daily Home Surface
  • PAT-00002 / PAT-002 Quick Capture
  • PAT-00004 / PAT-004 Progressive Detail
  • PAT-00006 / PAT-006 Object Status List

Handoff To Other Skills

  • Use information-architect after the product object model is known.
  • Use interaction-designer when flow mechanics or state transitions need definition.
  • Use mobile-ux-expert for touch-first layout and primary action placement.
  • Use design-reviewer after a proposal, prototype, or implementation exists.

Frequently asked questions

What does the Product Designer AI skill do?

Frame product direction for consumer workflows. Use when a feature needs a user goal, primary action, core object model, state coverage, or research-backed pattern selection before UI design.

Why use Product Designer on TypingMind?

Because you install it once and use it with any model. Product Designer 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 Product Designer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/dev-ik/ai-design-rules/tree/main/skills/product-designer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Product Designer?

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 Product Designer?

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

Is the Product Designer AI skill free?

Yes. It is published on GitHub by dev-ik 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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