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Drawio Skill

Agent skill that turns natural language, code, Terraform/K8s, SQL, OpenAPI, AsyncAPI, Protobuf and GraphQL sources into editable, tested draw.io architecture diagrams:…

Install

$npx skills add Agents365-ai/drawio-skill -g
Claude Code
claude mcp add drawio-skill -- npx skills add Agents365-ai/drawio-skill -g
Cursor / Claude Desktop (mcp.json)
{
  "mcpServers": {
    "drawio-skill": {
      "command": "npx",
      "args": [
        "skills",
        "add",
        "Agents365-ai/drawio-skill",
        "-g"
      ]
    }
  }
}

Install command taken from the project's README or registry entry. Always review code before running it.

drawio-skill — From Text to Professional Diagrams

English · 中文 · 📖 Online Docs

A skill that turns natural language and real system sources into maintainable .drawio architecture models. Beyond generation and export, it incrementally synchronizes without discarding manual layout, projects multiple views from one model, enforces architecture contracts, queries dependencies, simulates failure propagation, and publishes dependency-free interactive walkthroughs. Works with Claude Code, Cursor, Copilot, OpenClaw, Codex, Autohand Code, Hermes, and any agent compatible with the Agent Skills format.

✨ Highlights

From a prompt

  • Describe it, get an editable .drawio — the skill plans the layout, writes the XML, exports, then self-checks its own PNG and auto-fixes overlaps, clipped labels, and stacked edges (up to 2 rounds), with up to 5 rounds of your feedback
  • Mermaid → native .drawio (draw.io ≥ 30) — author 28 standard types as Mermaid text (mindmap, gantt, timeline, journey, pie, sankey, kanban…) and the CLI converts them into a laid-out, editable .drawio: structure in, layout free
  • Whiteboard photo / screenshot → editable diagram — snap a legacy PNG or a physical whiteboard, let vision extract the graph, and raster2drawio.py rebuilds it as a real, editable .drawio honouring the original layout
  • 11 diagram type presets — ERD, UML Class, Sequence, C4, Architecture, ML/Deep Learning, Flowchart, SysML, BPMN, Network Topology, Cross-Functional Swimlane

From real sources

  • Visualize a codebase — import graphs for Python / JS-TS / Go / Rust and Python class hierarchies, with Graphviz placement, transitive reduction, and nested module containers

  • IaC and live infrastructure — Terraform, Kubernetes, and docker-compose configs become diagrams with official AWS / Azure / GCP / K8s icons; snapshot what's actually deployed from terraform show -json, docker inspect, or kubectl get -o json

  • Schemas and pipelines — SQL DDL → ER diagram, OpenAPI/Swagger → API diagram coloured by HTTP method, AsyncAPI → event-driven architecture diagram, Protocol Buffers → message/service diagram, GraphQL SDL → entity type diagram, GitHub Actions / GitLab CI → pipeline DAG

  • Deterministic engines — sequence diagrams with computed lifelines and activation bars; multi-page C4 models with click-to-drill-down

Keep it true over time

  • Architecture digital twin / Diagram IR — separate meaning, provenance, and geometry; project executive, system, deployment, data-flow, and security views from one model
  • Incremental sync without losing manual layout — diagramctl sync updates changed nodes/relations while preserving tuned coordinates, styles, and annotations; removals stay reviewable by default
  • Diagram-as-Test, in CI — YAML/JSON architecture rules (Internet-to-database access, cycles, orphans, trust boundaries, contrast…) plus an official GitHub Action that enforces them on every PR, and a PR action that renders visual diffs
  • Query, review, what-if — query components/owners/paths, spot articulation points and high coupling, simulate failure propagation, publish an accessible Story walkthrough
  • Drift and history — colour-coded diffs between two diagrams or two live snapshots; a time-lapse player of how a codebase's architecture grew

Share and restyle

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