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Common Architecture Diagramming

Community
HoangNguyen0403
common-architecture-diagramming

Draw architecture diagrams as editable draw.io files with a fixed house style, C4 levels, and evidence-tagged shapes. Use when producing a system context, container, deployment, data flow, sequence, or state diagram, or redrawing an ASCII or Mermaid one.

Overview

PublisherHoangNguyen0403
Repositoryagent-skills-standard
Skill namecommon-architecture-diagramming
Stars
569
Forks
164
Bundled files
31
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • 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.

  • 31 bundled files

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

  • Open source

    Published by HoangNguyen0403 on GitHub. Read the source before you install it.

Installation

Install the Common Architecture Diagramming 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/HoangNguyen0403/agent-skills-standard.git /tmp/agent-skills-standard
mkdir -p .claude/skills
cp -r /tmp/agent-skills-standard/skills/common/common-architecture-diagramming .claude/skills/common-architecture-diagramming
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Common Architecture Diagramming 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 Common Architecture Diagramming 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 Common Architecture Diagramming 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.

Architecture Diagramming Standard

Priority: P1 (HIGH)

Pipeline

Never hand-write mxGraph XML. Write a spec; the scripts own every visual decision, so diagrams stay identical across authors, repositories, and sessions.

  1. Write spec.json — schema in diagram-spec.md. For an ERD, generate it: python3 scripts/schema_to_spec.py db/schema.sql --title "<System> — ERD" -o spec.json
  2. python3 scripts/validate_spec.py spec.json
  3. python3 scripts/render_drawio.py spec.json -o docs/architecture/<slug>.drawio --strict (exit 2 = a layout finding; change the spec, per layout-rules.md)
  4. Export the image: a draw.io MCP tool if the session has one, else python3 scripts/export_drawio.py docs/architecture/<slug>.drawio -f png -o docs/architecture/<slug>.png, else ship the .drawio and say the image was not exported. See export paths.

Commit the .drawio as the source of truth; the image is a copy for a deck.

Guidelines

  • Name the audience and the decision before drawing anything.
  • One C4 level per diagram: context, container, or component, never mixed.
  • Pick the type from the message, not from habit. See diagram-selection.md.
  • Evidence per node as path:line. A node with no evidence renders dashed and marked UNVERIFIED — leave the flag showing rather than asserting a guess.
  • Put the number on the box. metric carries the load or SLO that sized the node, constraint says why it exists; never invent either.
  • Label every edge with its protocol or event; use style: async for events.
  • Cloud icons only where verified. gcp:* and aws:* are official icons; every other vendor is a cloud:* kind with the service named in sublabel. No Azure logos exist in the bundle, so Azure is always cloud:*.
  • Exec audience caps at 12 nodes. Past that, split by level or by flow.
  • Legend and title block are generated. Do not remove or duplicate them.
  • Refine in draw.io, not in XML. Re-running the renderer overwrites layout tweaks.

Anti-Patterns

  • No hand-written XML: Write the spec, run the renderer.
  • No invented boxes: Omit what the evidence does not support.
  • No mixed levels: Table columns never appear in a context diagram.
  • No unlabeled arrows: State the protocol or the event.
  • No mystery acronyms: Expand every abbreviation on first use.
  • No orphan nodes: Connect it or cut it.

Red Flags

ThoughtReality
"It is one box, I will write the XML"The renderer owns style, legend, and title block. Use it.
"Close enough, I will guess this service"Guesses ship as facts. Omit the evidence and let it render UNVERIFIED.
"Managers want the whole system on one page"Past 12 nodes they stop reading. Split it.

References

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 Common Architecture Diagramming AI skill do?

Draw architecture diagrams as editable draw.io files with a fixed house style, C4 levels, and evidence-tagged shapes. Use when producing a system context, container, deployment, data flow, sequence, or state diagram, or redrawing an ASCII or Mermaid one.

Why use Common Architecture Diagramming on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HoangNguyen0403/agent-skills-standard/tree/develop/skills/common/common-architecture-diagramming. 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 Common Architecture Diagramming?

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 Common Architecture Diagramming?

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

Is the Common Architecture Diagramming AI skill free?

Yes. It is published on GitHub by HoangNguyen0403 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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