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Living Architecture Map — auto-generate Mermaid diagrams of your codebase. Use when user wants to visualize architecture, understand code structure, generate diagrams, or document system design.

Overview

PublisherHouseofmvps
Repositoryultraship
Skill namearchitecture
Stars
122
Forks
14
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 Houseofmvps on GitHub. Read the source before you install it.

Installation

Install the Architecture 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/Houseofmvps/ultraship.git /tmp/ultraship
mkdir -p .claude/skills
cp -r /tmp/ultraship/skills/architecture .claude/skills/architecture
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Architecture 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 Architecture 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 Architecture 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.

Living Architecture Map

Auto-generates and maintains architecture diagrams from your actual code. Always up-to-date.

Process

Phase 1: Scan

bash
node ${CLAUDE_PLUGIN_ROOT}/tools/architecture-mapper.mjs <project-directory>

Parse the JSON output for architecture data and diagrams.

Phase 2: Present Diagrams

Display each Mermaid diagram with context:

System Architecture: High-level view of all components and how they connect.

mermaid
[system diagram from tool output]

API Route Map: All endpoints organized by resource.

mermaid
[routes diagram from tool output]

Database Schema: Entity-relationship diagram of all tables and relations.

mermaid
[database ER diagram from tool output]

Data Flow: Sequence diagram showing how a typical request flows through the system.

mermaid
[data flow diagram from tool output]

Phase 3: Architecture Analysis

Based on the scanned data, provide analysis:

Strengths:

  • Clear layer separation
  • No circular dependencies
  • Well-organized middleware chain

Concerns:

  • Circular dependencies found (list them)
  • Orphan modules (files imported by nothing)
  • Large files that may need splitting
  • Missing middleware (no auth, no rate limiting, etc.)

Service Dependencies: List all external services and how they're used. Flag any that are single points of failure.

Phase 4: Save Diagrams

Save architecture documentation:

  1. Create docs/architecture/ directory
  2. Save docs/architecture/ARCHITECTURE.md with all diagrams
  3. Save individual diagram files if needed

The document should be self-contained and renderable in GitHub (GitHub supports Mermaid in markdown).

Phase 5: Recommendations

Based on architecture analysis:

  1. Circular dependencies — suggest how to break cycles
  2. Orphan modules — suggest removal or integration
  3. Missing patterns — suggest middleware, error handling, or caching if absent
  4. Scalability concerns — identify bottlenecks (single database, no caching, synchronous processing)

Keeping Diagrams Updated

Recommend running /architecture after any significant structural change:

  • Adding new API routes
  • Adding new database tables
  • Integrating new external services
  • Major refactors

The diagrams are generated from code, so they're always accurate when re-run.

Key Principle

The map IS the territory. Architecture diagrams that drift from reality are worse than no diagrams. Because these are auto-generated from code, they're always truthful.

Frequently asked questions

What does the Architecture AI skill do?

Living Architecture Map — auto-generate Mermaid diagrams of your codebase. Use when user wants to visualize architecture, understand code structure, generate diagrams, or document system design.

Why use Architecture on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Houseofmvps/ultraship/tree/main/skills/architecture. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Architecture?

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 Architecture?

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

Is the Architecture AI skill free?

Yes. It is published on GitHub by Houseofmvps 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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