Generate draw.io diagrams from natural language — 11 presets (UML, SysML/MBSE, BPMN, network, C4…), 36 tools: codebase/CI/infra-to-diagram, image→editable diagram, mind maps, build-up animation, exec-view compression, click-through runbooks, PR diff bot. Vision self-check, 10,000+ shapes. Exports PNG/SVG/PDF/JPG.
drawio-skill — From Text to Professional Diagrams
English · 中文 · 📖 Online Docs
A skill that turns natural-language descriptions into .drawio XML and exports them to PNG / SVG / PDF / JPG via the native draw.io desktop CLI. It can also turn an existing codebase (Python / JS-TS / Go / Rust), Terraform / Kubernetes / docker-compose infrastructure, or a SQL schema into an auto-laid-out diagram. Works with Claude Code, Cursor, Copilot, OpenClaw, Codex, Autohand Code, Hermes, and any agent compatible with the Agent Skills format.
✨ Highlights
- 11 diagram type presets — ERD, UML Class, Sequence, C4, Architecture, ML/Deep Learning, Flowchart, SysML (BDD / IBD / Requirement / Parametric), BPMN, Network Topology, Cross-Functional Swimlane
- 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 - Visualize a codebase — extract and auto-lay-out the structure of a Python / JS-TS / Go / Rust project (import graphs) or a Python class hierarchy — Graphviz placement, transitive reduction, nested module containers
- IaC → architecture diagram — turn Terraform configs, Kubernetes manifests, or docker-compose files into an architecture diagram where every resource renders as its official AWS / Azure / GCP / K8s icon, edges derived from actual references (role ARNs, selectors, volume mounts)
- SQL DDL → ER diagram — parse
CREATE TABLEstatements into per-table nodes with PK/FK markers and crow's-foot foreign-key edges - Deterministic sequence diagrams — describe participants + messages as JSON; lifelines, auto-tracked activation bars, and arrows are computed, never hand-placed
- C4 model with drill-down — one command generates the multi-page System Context → Container → Component set with official C4 shapes; parent elements click through to their child page
- Search 10,000+ official shapes — resolve the exact AWS / Azure / GCP / Cisco / Kubernetes / UML / BPMN icon style instead of guessing (no more blank-box
shape=mxgraph.*typos) - AI / LLM brand logos — 321 logos (OpenAI, Claude, Gemini, Mistral, Llama, Ollama, LangChain…) that draw.io has none of, plus 18 data-store brands (Redis, Postgres, Qdrant, Milvus…) for LLM/RAG architecture diagrams
- Self-check + auto-fix — reads its own PNG output and auto-fixes overlaps, clipped labels, stacked edges, and more (up to 2 rounds)
- Iterative feedback loop — up to 5 rounds of targeted refinement
- Style presets — capture your visual style from a
.drawiofile or image, reuse on demand - Clean layout — grid-aligned, spacing scales with diagram size, connectors routed clear of nodes
- Multi-agent, zero-config — runs from a single SKILL.md; no MCP server, no background daemon (the optional
npxinstaller needs Node, the skill itself does not)
🗺️ Feature Map
A bird's-eye view of everything the skill does — diagram types, import sources, layout engines, styling, export formats, and repurposing — in one map. Fittingly, this map was itself drawn with drawio-skill.
🖼️ Examples
[!TIP]
The hero image above was generated from this single prompt:
Create a microservices e-commerce architecture with Mobile/Web/Admin clients,
API Gateway (auth + rate limiting + routing), Auth/User/Order/Product/Payment
services, Kafka message queue, Notification service, and User DB / Order DB /
Product DB / Redis Cache / Stripe APIThe skill is designed to route edges cleanly across different topologies, avoiding lines that cross through shapes:
 Star · 7 nodes Central message broker with 6 microservices radiating outward, no edge crossings on this example. |
 Layered · 10 nodes / 4 tiers E-commerce stack with horizontal and diagonal cross-connections routed via corridors. |
 Ring · 8 nodes CI/CD pipeline with a closed loop and 2 spur branches flowing along the perimeter. |
It also speaks Mermaid — standard types (flowchart, mindmap, kanban, gitGraph, timeline…) convert straight to native, editable .drawio. Here's a Kanban board (this project's own roadmap) generated from a few lines of Mermaid:
Tube-Map Mode restyles a pipeline or journey as a London-Underground-style metro map — coloured lines, octilinear (H/V/45°) routing, and white interchange circles. Here's the skill's own flow (this map is assets/tubemap.json, ~20 lines):
Full walkthrough in docs/USAGE.md.
🚀 Installation
1. Install the draw.io desktop CLI
| Platform | Command | |----------|---------| | macOS | brew install --cask drawio | | Windows | Download installer | | Linux | .deb/.rpm from releases; sudo apt install xvfb for headless |
Verify with drawio --version. Version ≥ 30 recommended — it unlocks Mermaid → .drawio conversion and the ELK --layout pass (both unavailable on ≤ 29). On WSL2 the CLI is the Windows desktop exe reached via /mnt/c — the skill detects this automatically (see troubleshooting). Full recipes in docs/INSTALLCLI.md.
2. Install the skill
# Any agent (Claude Code, Cursor, Copilot, ...)
npx skills add Agents365-ai/365-skills -g# Claude Code plugin marketplace
> /plugin marketplace add Agents365-ai/365-skills
> /plugin install drawio# Manual install
git clone https://github.com/Agents365-ai/drawio-skill.git \
~/.claude/skills/drawio-skill
Autohand Code global install
git clone https://github.com/Agents365-ai/drawio-skill.git \
~/.autohand/skills/drawio-skill
Autohand Code project-level install
git clone https://github.com/Agents365-ai/drawio-skill.git \
.autohand/skills/drawio-skillAutohand Code also supports autohand --skill-install for cataloged skills, with --project for workspace-level installs. Until this skill is listed there, use the direct clone path above.
Also indexed on SkillsMP and ClawHub.
Updating: /plugin update drawio (Claude Code), skills update drawio-skill (SkillsMP), clawhub update drawio-pro-skill (OpenClaw), or git pull for manual installs — see docs/INSTALLSKILL.md#updates. Release history in CHANGELOG.md.
⚡ Quick Start
After installation, just describe what you want. For example, an ML model:
Draw a Transformer encoder-decoder for machine translation: 6-layer encoder
with self-attention, 6-layer decoder with cross-attention, input embeddings
(batch × 512 × 768), positional encoding, and a final output projection.
Annotate tensor shapes between layers and color-code by layer type.The skill plans the layout, generates the .drawio XML, exports to your chosen format, self-checks the result, and lets you iterate.
🗺️ Visualize Code & Infrastructure
Beyond hand-authored diagrams, the skill turns existing code, infrastructure, and schemas into diagrams — no manual coordinates. Just ask:
"Visualize the module structure of this Python project" · "Draw the class hierarchy of mypackage"
↑ Python's logging package as a class hierarchy — one command, modules auto-boxed, every inheritance edge resolved.
Under the hood it runs a bundled extractor → auto-layout → validate pipeline:
# Import graph — Python / JS-TS / Go / Rust
python3 scripts/pyimports.py myproject --group -o graph.json
python3 scripts/jsimports.py ./src --group -o graph.json
python3 scripts/goimports.py ./module --group -o graph.json
python3 scripts/rustimports.py ./crate --group -o graph.json
Python class-inheritance hierarchy
python3 scripts/pyclasses.py mypackage --group -o graph.json
Infrastructure as Code — official cloud icons resolved automatically
python3 scripts/tfimports.py ./infra -o graph.json # Terraform → AWS/Azure/GCP icons
python3 scripts/k8simports.py ./manifests -o graph.json # K8s YAML/JSON → kind icons
python3 scripts/composeimports.py compose.yml -o graph.json # services + named volumes
Live infrastructure — draw what's ACTUALLY running / deployed
terraform show -json | python3 scripts/tfstate.py - -o graph.json # deployed cloud
docker inspect $(docker ps -q)| python3 scripts/dockerimports.py - -o graph.json # running containers
kubectl get all,ing,cm,secret,pvc -o json | python3 scripts/k8simports.py - -o graph.json # live cluster
Data & interactions
python3 scripts/sqlerd.py schema.sql -o graph.json # SQL DDL → ER diagram
python3 scripts/ciimports.py . -o graph.json # GitHub Actions + GitLab CI -> pipeline DAG
python3 scripts/openapiimports.py openapi.yaml -o graph.json # OpenAPI/Swagger → API diagram (by method)
python3 scripts/seqlayout.py seq.json -o sequence.drawio # sequence diagram, direct to .drawio
python3 scripts/c4.py c4.json -o c4.drawio # C4 model, multi-page + drill-down
Diff two diagrams / snapshots → colour-coded "what changed"
python3 scripts/drawiodiff.py old.drawio new.drawio -o graph.json # +added -removed ~changed
Architecture time-lapse → self-contained HTML player of how a codebase grew
python3 scripts/timelapse.py src --importer pyimports # → architecture-evolution.html
Reverse: describe an existing .drawio as structured Markdown (README / PR summary)
python3 scripts/explain.py architecture.drawio -o architecture.md
Diagram → PowerPoint deck (one page per slide; C4 model → presentation)
python3 scripts/drawio2pptx.py c4.drawio -o c4.pptx # needs: pip install python-pptx
Interactive HTML viewer — pan/zoom/search/tabs + working drill-down links, one file
python3 scripts/drawiohtml.py c4.drawio -o c4.html
Animated data-flow SVG — edges "flow" (marching ants); renders on GitHub
python3 scripts/svgflow.py architecture.drawio -o flow.svg
Reverse: .drawio → Mermaid flowchart (diagrams-as-code GitHub renders)
python3 scripts/drawio2mermaid.py architecture.drawio --fenced -o arch.md
Language variant: extract labels → translate values → apply (layout untouched)
python3 scripts/relabel.py architecture.drawio --extract -o labels.json
python3 scripts/relabel.py architecture.drawio --map labels.json -o architecture_cn.drawio
Re-theme an existing .drawio with a style preset (e.g. dark mode)
python3 scripts/restyle.py architecture.drawio --preset dark
Colour an existing .drawio by data → cost / latency / traffic heat map
python3 scripts/heatmap.py architecture.drawio -m latency.csv --size -o hot.drawio
any extractor → auto-layout → editable .drawio
python3 scripts/autolayout.py graph.json -o diagram.drawio
Image → editable .drawio — your vision extracts the graph JSON, this rebuilds it
python3 scripts/raster2drawio.py whiteboard-graph.json -o out.drawio
Watch a diagram build itself, node by node → HTML player (+ optional GIF)
python3 scripts/buildup.py architecture.drawio --gif build.gif # → buildup.html
Big diagram → boardroom exec summary (clustered) + click-to-drill-down to full
python3 scripts/compress.py big.drawio -o exec.drawio
Decision-tree flowchart → click-through HTML triage runbook (no draw.io CLI needed)
python3 scripts/runbook.py triage.drawio -o triage.html
CI: render base/head/diff PNGs + Markdown report for every .drawio a PR changed
python3 scripts/prdiff.py --base origin/main --head HEAD -o drawio-pr/report.md
Tube-Map Mode — restyle a pipeline / journey as a metro / subway map
python3 scripts/tubemap.py metro.json -o metro.drawio| Piece | What it does | |---|---| | 13 extractors | import graphs for Python · JS/TS · Go · Rust, Python class inheritance, Terraform / Kubernetes / docker-compose resource graphs (official cloud icons), SQL DDL → ERD, OpenAPI / Swagger → API diagram (operations coloured by HTTP method + schemas), CI pipelines → DAG (GitHub Actions needs: graphs + GitLab stages, with triggers, matrix sizes, reusable-workflow calls), and live infra from terraform show -json / docker inspect / kubectl get -o json (draw what's actually deployed) | | Diagram diff | drawiodiff.py compares two .drawio (or two live snapshots) into one colour-coded graph — added=green, removed=red, changed=orange — so you can see architecture / infra drift at a glance | | Language variants | relabel.py swaps every label via a JSON map with layout/styles/ids untouched — --extract dumps all labels, translate the values, --map applies them. One diagram → EN + CN twins for bilingual docs | | Re-theme | restyle.py applies a style preset (built-in dark/corporate/… or your own) to an existing .drawio — palette remapped by hue so same-colored nodes stay grouped; layout and edge routing untouched | | Metric heat map | heatmap.py recolours an existing .drawio from a CSV/JSON of per-node values — cost / latency / traffic / error-rate shaded low→high on a gradient (optional size-by-value + legend), matched by cell id or label | | Architecture time-lapse | timelapse.py re-runs an importer across a repo's git history and assembles a self-contained HTML player — watch modules & edges appear over time (▶ play / ‹ › step) | | Diagram → Markdown | explain.py reverses a .drawio into a structured description — components by tier, relations, per-page for C4 — for dropping an architecture summary into a README or PR | | Interactive viewer | drawiohtml.py publishes a .drawio as one self-contained HTML — page tabs, drag-pan, wheel-zoom, node search, and a C4 model's drill-down links keep working. Share the file; no draw.io, no server | | Diagram → PowerPoint | drawio2pptx.py turns a multi-page diagram into a 16:9 deck (one page per slide, page name as title) — a C4 model becomes a ready-to-present slideshow | | Animated data-flow | svgflow.py makes a diagram's edges flow (marching-ants animation along each arrow) — a self-contained looping SVG that renders on GitHub, in docs, or as a slide background | | Diagram → Mermaid | drawio2mermaid.py converts a .drawio into a Mermaid flowchart (containers → subgraphs, edge labels kept) — paste it into Markdown as diagrams-as-code that GitHub renders natively | | Sequence engine | seqlayout.py computes lifeline / activation-bar / arrow geometry from a message list — no Graphviz, no hand placement | | Auto-layout | Graphviz places nodes and routes orthogonal edges around them — removes the manual-coordinate ceiling for large graphs. --tune tries both directions and keeps the more readable one | | Transitive reduction | drops edges implied by a longer path, turning a dense hairball into a traceable graph (asyncio: 149 → 46 edges) | | Nested containers | --group boxes modules by sub-package, nested for deep package trees | | Deterministic validator | validate.py lints the .drawio (dangling edges, duplicate ids, overlaps) before the visual self-check |
Layout needs Graphviz (brew install graphviz / apt install graphviz) — optional; everything else works without it. Full format + flag reference in references/autolayout.md. Regenerate, validate (--strict gate) and render headlessly in CI: docs/CI.md.
🧩 Supported Diagram Types
| Category | Examples | Notable features | |---|---|---| | Architecture | microservices, cloud (AWS/GCP/Azure), network topology, deployment | Tier-based swimlanes, hub-center strategy | | C4 model | system context, containers, components | Multi-page .drawio, click-to-drill-down links | | ML / Deep Learning | Transformer, CNN, LSTM, GRU | Tensor shape annotations, layer-type color coding | | Flowcharts | business processes, workflows, decision trees, state machines | Semantic shapes (parallelogram I/O, diamond decisions) | | UML | class diagrams, sequence diagrams | Inheritance / composition / aggregation arrows; lifelines + activation boxes | | SysML / MBSE | block definition (bdd), internal block (ibd), requirement (req), parametric (par) | «block» / «requirement» compartments, satisfy/derive/verify edges, native mxgraph.sysml.* ports & flows | | BPMN | business processes, pools & lanes | Native mxgraph.bpmn.* events/tasks/gateways, sequence vs message flows | | Network topology | LAN/WAN, subnets, DMZ | mxgraph.networks.* device shapes, zone containers, link labels; Cisco/rack via shape search | | Cross-functional swimlane | who-does-what processes, handoffs | Pool + role lanes, flowchart vocabulary, orthogonal handoff edges | | Data | ER diagrams, data flow diagrams (DFD) | Table containers, PK/FK notation | | Mermaid-authored | mind maps, gantt, timeline, journey, pie, sankey, kanban + 20 more | Native CLI conversion (≥ v30) — structure only, layout free | | Other | org charts, wireframes | — |
🔍 Shape Search
Need a real AWS / Azure / GCP / Cisco / Kubernetes / UML / BPMN icon? The skill searches 10,000+ official draw.io shapes for the exact style string — so vendor icons render correctly instead of falling back to a blank box from a guessed shape=mxgraph.* name.
"Add an AWS Lambda wired to an S3 bucket" · "Use the real Kubernetes pod icon"
python3 scripts/shapesearch.py "aws lambda" --limit 5
→ Lambda (77x93)
outlineConnect=0;...;shape=mxgraph.aws3.lambda;fillColor=#F58534;...
↑ A serverless AWS architecture — every icon is the real official draw.io shape resolved by shapesearch.py, not a hand-guessed shape= string.
Covers AWS / Azure / GCP / Cisco / Kubernetes / UML / BPMN / ER / electrical / P&ID and the general shape sets. Hand-writable style cheatsheet + search usage in references/shapes.md.
🤖 AI / LLM Brand Logos
draw.io ships no modern AI/LLM logos, so an LLM-app diagram renders as generic boxes. aiicons.py resolves a brand name to a draw.io image style for any of 321 logos (OpenAI, Claude, Gemini, Mistral, Llama, Cohere, DeepSeek, Qwen, Ollama, LangChain, HuggingFace…) from lobe-icons (MIT), plus 18 data-store brands (Redis, Postgres, MongoDB, Qdrant, Milvus, Supabase…) via simple-icons (CC0) for RAG stacks.
python3 scripts/aiicons.py "claude" --json # CDN-referenced (default)
python3 scripts/aiicons.py "openai" --embed # self-contained data URI 
↑ A multi-provider LLM app — every brand logo resolved by aiicons.py. Icons are referenced from the unpkg CDN by default (network needed at render time); --embed inlines them for offline use. Logos are trademarks of their owners, used for identification only.
🎨 Style Presets
Capture a visual style once, reuse it everywhere. Five presets are built in — default, corporate, handdrawn, colorblind-safe (Okabe-Ito palette), dark — and you can teach the skill your own style from a .drawio file or a flat image:
Draw a microservices architecture using my "corporate" styleLearn my style from ~/diagrams/brand.drawio as "mybrand"The skill extracts colors, shapes, fonts, and edge style, renders a preview, and only saves the preset after you approve. Full preset-management commands in docs/STYLE_PRESETS.md.
🔄 How it works
Behind the scenes: check dependencies → plan layout → generate .drawio XML → export draft PNG → self-check + auto-fix (up to 2 rounds) → show to user → 5-round feedback loop until approved → final export.
🆚 Comparison
vs Native Agent (no skill)
| Feature | Native agent | drawio-skill | |---|---|---| | Self-check after export | ❌ | ✅ reads PNG, auto-fixes 6 issue types | | Iterative review loop | ❌ manual re-prompt | ✅ targeted edits, 5-round safety valve | | Diagram type presets | ❌ | ✅ 7 presets (ERD, UML, Seq, C4, Arch, ML, Flow) | | Mermaid → editable .drawio | ❌ | ✅ 28 types via native CLI conversion (≥ v30) | | Visualize a codebase | ❌ | ✅ import graphs (Py/JS/Go/Rust) + class diagrams | | IaC → architecture diagram | ❌ | ✅ Terraform / K8s / compose → official cloud icons | | SQL DDL → ER diagram | ❌ | ✅ CREATE TABLE → PK/FK tables, crow's-foot edges | | Sequence diagrams | ❌ hand-placed coordinates | ✅ deterministic geometry engine (seqlayout.py) | | C4 model | ❌ | ✅ multi-page Context→Container→Component with click-to-drill-down | | Auto-layout for large graphs | ❌ hand-places, overlaps | ✅ Graphviz placement, ortho routing, nested containers | | Structural validation | ❌ | ✅ deterministic .drawio linter | | Official shape search | ❌ guesses, blank boxes | ✅ exact style for 10k+ AWS/Azure/GCP/UML shapes | | AI/LLM brand logos | ❌ none | ✅ 321 AI + 18 data-store logos via aiicons.py | | Grid-aligned layout | ❌ | ✅ 10px snap, routing corridors | | Color palette | random / inconsistent | ✅ 7-color semantic system | | Style presets | ❌ | ✅ learn from .drawio file or image |
vs Other draw.io Skills & Tools
| Feature | drawio-skill | jgraph/drawio-mcp (official)
skills/drawio-skill/ | ✅ | ✅ desktop-only mode | ❌ needs plugin install |
Using the official jgraph plugin? jgraph/drawio-mcp now ships an official Claude Code plugin (/plugin install drawio@drawio) that also generates.drawioand exports via the desktop CLI. drawio-skill is complementary — reach for it when you want the code / IaC / SQL / OpenAPI importers, AI-brand logos, deterministic sequence & C4 generators, self-check + review loop, and the interactive HTML viewer, all from a single SKILL.md with no MCP server.
Full comparison + key-advantages summary in docs/COMPARISON.md (with audit timestamp).
🎯 When to use (and when not to)
Good fit:
- Polished, precise diagrams — stakeholder decks, architecture, network topology, strict UML, ER diagrams
- Solid opaque fills, 10,000+ official shapes, branded icons (AWS / Azure / GCP / Cisco / Kubernetes + AI/LLM logos), swimlanes, and custom geometry
- Anything you'll export to PNG / SVG / PDF and keep editable
- A casual, hand-drawn / whiteboard look → excalidraw-skill or tldraw-skill
- Diagrams-as-code that live in git and render in Markdown → mermaid-skill (general) or plantuml-skill (UML)
- Freeform infinite-canvas sketching / freehand strokes → tldraw-skill
🔗 Related Skills
Part of the Agents365-ai diagram-skill family — pick the right tool for the job:
| Skill | Style | Best for | |---|---|---| | excalidraw-skill | Hand-drawn / sketchy | Whiteboard mockups, informal diagrams | | mermaid-skill | Text-based, auto-layout | README-embeddable, version-control friendly | | plantuml-skill | UML-focused | Class / sequence diagrams in CI pipelines | | tldraw-skill | Whiteboard collaboration | Casual sketches, FigJam-style boards |
❤️ Support
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👤 Author
Agents365-ai
- GitHub: https://github.com/Agents365-ai
- Bilibili: https://space.bilibili.com/441831884
