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Prompt Architect

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dev-ik
prompt-architect

Create or review graph-backed prompts for design agents. Use when prompts need explicit rules, patterns, output contracts, scope constraints, review expectations, or traceable knowledge references.

Overview

Publisherdev-ik
Repositoryai-design-rules
Skill nameprompt-architect
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 Prompt Architect 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/prompt-architect
  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/prompt-architect .claude/skills/prompt-architect
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prompt Architect 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 Prompt Architect 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 Prompt Architect 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.

Prompt Architect Skill

Role

Design and review prompts that apply existing AI Design Context knowledge without inventing new design advice.

Mission

Turn rules, patterns, reference projects, and review expectations into agent instructions that are specific, traceable, and safe to execute.

When To Use

  • A prompt needs to guide agents through product design or review.
  • A prompt must reference existing rules and patterns.
  • Prompt output is vague, too broad, or disconnected from the graph.
  • A reference project prompt needs maintenance.

When Not To Use

  • A new rule, pattern, or research object is needed first.
  • The task is direct UI implementation.
  • The request is only final design QA.

Inputs

  • Target task and agent audience.
  • Required rules and patterns.
  • Reference project context if applicable.
  • Evidence-backed visual direction or agent lifecycle requirements when applicable.
  • Known constraints and expected output format.

Process

  1. Define the prompt objective.
  2. List required rules and patterns by ID.
  3. State what the agent must not invent.
  4. Define input requirements.
  5. Require source or artifact evidence for visual-reference claims.
  6. Define output format, states, responsive assumptions, and review criteria.
  7. Add traceability expectations and explicit knowledge gaps.
  8. Hand off to design review or knowledge graph review.

Output Format

md
## Prompt Architecture
- Objective:
- Agent audience:
- Required inputs:

## Required Knowledge
- Rules:
- Patterns:
- Reference project:
- Reference evidence:

## Output Contract
- Sections:
- Validation:
- Forbidden output:
- Evidence gaps:

## Handoff
- Next skill:
- Reason:

Quality Checklist

  • Prompt has one clear job.
  • Prompt references existing rules and patterns.
  • Prompt tells agents what not to invent.
  • Output format is explicit.
  • Review criteria are included.
  • Reference project usage is traceable.
  • Visual direction and agentic lifecycle claims are grounded in applicable research and rules.

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-00003 / PAT-003 Mobile Primary Action
  • PAT-00004 / PAT-004 Progressive Detail
  • PAT-00005 / PAT-005 Context-Preserving Preview
  • PAT-00006 / PAT-006 Object Status List

Handoff To Other Skills

  • Use product-designer to clarify product intent before prompt writing.
  • Use design-reviewer to test prompt output quality.
  • Use knowledge-graph-architect to validate metadata and relationships.
  • Use accessibility-reviewer if prompt output includes UI review obligations.

Frequently asked questions

What does the Prompt Architect AI skill do?

Create or review graph-backed prompts for design agents. Use when prompts need explicit rules, patterns, output contracts, scope constraints, review expectations, or traceable knowledge references.

Why use Prompt Architect on TypingMind?

Because you install it once and use it with any model. Prompt Architect 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 Prompt Architect in TypingMind?

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

Which AI models can use Prompt Architect?

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 Prompt Architect?

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

Is the Prompt Architect 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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