drawio-skill

name	drawio-skill
version	2.1.0
description	Use when the user requests diagrams, flowcharts, architecture diagrams, ER diagrams, UML / sequence / class diagrams, SysML / MBSE diagrams (block definition, internal block, requirement, parametric), BPMN business process diagrams, swimlane / cross-functional flowcharts, network topology, cloud architecture from Terraform or Kubernetes manifests, ML/DL model figures (Transformer/CNN/LSTM), mind maps, or any visualization. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. Best suited when the diagram needs custom styling, rich shape vocabulary, swimlanes, or exportable images (PNG/SVG/PDF/JPG). Generates .drawio XML and exports locally via the native draw.io desktop CLI.
license	MIT
homepage	https://github.com/Agents365-ai/drawio-skill
compatibility	Requires draw.io desktop app CLI on PATH (macOS/Linux/Windows). Self-check step requires a vision-enabled model (e.g., Claude Sonnet/Opus); gracefully skipped if unavailable. Optional auto-layout (scripts/autolayout.py) needs Graphviz (dot).
platforms	["macos","linux","windows"]
metadata	{"openclaw":{"requires":{"anyBins":"[Truncated]"},"emoji":"📐","os":["darwin","linux","win32"],"install":["[Truncated]","[Truncated]"]},"hermes":{"tags":["drawio","diagram","flowchart","architecture","visualization","uml"],"category":"design","requires_tools":["drawio","draw.io"],"related_skills":["mermaid","excalidraw","plantuml"]},"author":"Agents365-ai","version":"2.1.0"}

Draw.io Diagrams

Overview

Generate .drawio XML files and export to PNG/SVG/PDF/JPG locally using the native draw.io desktop app CLI.

Supported formats: PNG, SVG, PDF, JPG — no browser automation needed.

PNG, SVG, and PDF exports support --embed-diagram (-e) — the exported file contains the full diagram XML, so opening it in draw.io recovers the editable diagram. Use double extensions (name.drawio.png) to signal embedded XML.

When to use / when NOT to use

Use this skill for: polished, precise diagrams (architecture, network, strict UML, ERD), anything needing solid opaque fills, 10,000+ stock/branded shapes, swimlanes, or custom geometry, exported as editable PNG/SVG/PDF.

Do NOT use it — route elsewhere — for:

• A casual hand-drawn / whiteboard look → excalidraw or tldraw.
• Diagrams-as-code that live in git / render in Markdown → mermaid (general) or plantuml (UML).
• Freeform infinite-canvas sketching or freehand strokes → tldraw.

Bundled resources

When the workflow references one of these, read it on demand — none of them need to be in context up front.

File	Read it when
references/toolbox.md	You're not sure which bundled script fits a request, or want to chain several — a map of all 31 scripts grouped by use-case (author / import code / import IaC / import API spec / live infra / compare / annotate / reverse-export / utilities) with an "I have X, I want Y → use Z" guide
references/xml-authoring.md	You're about to hand-write .drawio XML (workflow step 3) — file skeleton, shape/edge cells, containers, connection distribution, palette, spacing/grid rules. Not needed when a bundled generator writes the XML
references/mermaid-authoring.md	The diagram is a standard type with no custom styling/icon needs (flowchart, state, gantt, mindmap, timeline, journey, pie, …) and the CLI is ≥ v30 — author it as Mermaid text and let the CLI convert to native .drawio (structure only, layout free). Also documents the CLI's ELK --layout pass for XML
references/diagram-types.md	The user names a specific diagram type (ERD, UML class, sequence, C4, architecture, ML/DL, flowchart, SysML, BPMN, network topology, swimlane)
references/shapes.md + scripts/shapesearch.py	The diagram needs a specific shape — a cloud icon (AWS/Azure/GCP), Cisco/Kubernetes/network symbol, UML/BPMN/ER/electrical/P&ID element — or any time you'd otherwise guess a style= string. shapesearch.py "<keywords>" returns the exact official style for 10k+ shapes
scripts/aiicons.py	The diagram involves an AI/LLM brand (OpenAI, Claude, Gemini, Mistral, Llama, HuggingFace, Ollama, LangChain, …) — aiicons.py "<brand>" returns a draw.io image style for the brand logo (lobe-icons via CDN; --embed to inline). draw.io has no built-in AI logos. See references/shapes.md → "AI / LLM brand logos"
references/style-presets.md	The user asks to learn / save / list / set-default / delete a style preset, or you've resolved an active preset and need the application rules
references/style-extraction.md	You're inside the Learn flow and need the extraction procedure (called from style-presets.md)
references/troubleshooting.md	An export fails, vision rejects a PNG, or a rendering looks wrong
scripts/repair_png.py	After every -e PNG export — fixes draw.io's truncated IEND chunk (issue #8)
scripts/encode_drawio_url.py	The CLI is unavailable and you need a browser-fallback diagrams.net URL (--edit for an editable editor URL)
references/autolayout.md	The diagram is large or layout-heavy (dependency/call graph, code structure, >~15 nodes) and you want Graphviz to place nodes + route edges instead of hand-placing coordinates
scripts/pyimports.py · jsimports.py · goimports.py · rustimports.py	The user wants to visualize a Python, JS/TS, Go, or Rust project structure — extracts the import graph (transitive-reduced, optional --group containers, nested by sub-package) for autolayout
scripts/pyclasses.py	The user wants a Python class hierarchy / class diagram — extracts classes + inheritance edges (boxed by module with --group) for autolayout
scripts/tfimports.py · k8simports.py · composeimports.py	The user wants to visualize declared infrastructure (Terraform .tf, Kubernetes manifests, or docker-compose) — extracts the resource/service reference graph (official AWS/Azure/GCP/K8s icons for tf/k8s; service boxes + volume cylinders for compose) for autolayout
scripts/tfstate.py · dockerimports.py (+ k8simports.py)	The user wants to draw what is ACTUALLY running / deployed — pipe terraform show -json (deployed state), docker inspect $(docker ps -q) (live containers), or kubectl get all,ing,cm,secret,pvc -o json (live cluster, via k8simports) and get the real topology with the same official icons. See references/live-infra.md
scripts/drawiodiff.py	The user wants to compare / diff two diagrams or two snapshots ("what changed", infra drift) — drawiodiff.py old.drawio new.drawio -o diff.json emits a colour-coded graph (added=green, removed=red, changed=orange, same=grey) for autolayout. Matches by cell id (importer/live-snapshot output) or --by-label (hand-drawn)
scripts/timelapse.py	The user wants an architecture time-lapse / to see how a codebase's structure evolved over git history — timelapse.py <dir> --importer pyimports re-runs an importer at each sampled commit and assembles a self-contained HTML player (embedded frames, play/step controls). Best on a package with real import edges (point <dir> at the module root)
scripts/explain.py	The user wants to describe / document / summarize an existing .drawio in words (reverse of generating one) — explain.py diagram.drawio emits structured Markdown: components grouped by container/tier, relations (A —label→ B), per-page sections for multi-page/C4. Good for a README/PR summary or a text-only read-out
scripts/drawio2pptx.py	The user wants a PowerPoint deck / slides from a diagram — drawio2pptx.py diagram.drawio -o deck.pptx puts each page on its own 16:9 slide (page name as title), so a multi-page C4 model becomes a ready-to-present deck. Needs python-pptx (pip install python-pptx) + the draw.io CLI
scripts/drawiohtml.py	The user wants a shareable interactive viewer for a diagram (pan / zoom / search, no draw.io needed) — drawiohtml.py diagram.drawio -o viewer.html inlines every page's SVG into ONE self-contained HTML with page tabs, drag-pan, wheel-zoom, node search (Enter cycles + centres matches) and working drill-down links (a C4 model's data:page/id links switch tabs). No server, no external requests — send the file to anyone
scripts/svgflow.py	The user wants an animated / "flowing" diagram (data-flow, moving edges) — svgflow.py diagram.drawio -o flow.svg exports to SVG and makes every edge a marching-ants animation (dashes travel along the arrows). Self-contained looping .svg that renders on GitHub / any browser; --speed / --dash / --reverse
scripts/drawio2mermaid.py	The user wants to convert a .drawio into Mermaid text (diagrams-as-code for a Markdown file that GitHub renders) — drawio2mermaid.py diagram.drawio emits a flowchart (containers → subgraphs, edge labels kept, cylinder/rhombus shapes mapped); --fenced wraps in ```mermaid, multi-page → one graph per page. Structural only (styling/icons don't survive)
scripts/sqlerd.py	The user wants an ER diagram from SQL DDL — parses CREATE TABLE statements into per-table nodes (columns with PK/FK markers) and crow's-foot FK edges for autolayout
scripts/ciimports.py	The user wants a CI pipeline diagram (GitHub Actions workflows or GitLab CI) — ciimports.py <repo-root> reads .github/workflows/*.yml + .gitlab-ci.yml and emits jobs (runner, matrix size, reusable-workflow calls), needs: dependency edges, per-workflow trigger nodes, and stage/workflow containers for autolayout. Needs PyYAML
scripts/openapiimports.py	The user wants an API diagram from an OpenAPI / Swagger spec — openapiimports.py spec.yaml maps each operation to a node coloured by HTTP method (GET blue, POST green, PUT/PATCH orange, DELETE red) plus one node per component schema, with edges from operations to the schemas they use and between nested schemas. --group boxes by tag, --no-schemas shows just the endpoint surface; feeds autolayout
scripts/heatmap.py	The user wants to colour an existing .drawio by data (a cost / latency / traffic / error-rate heat map) — heatmap.py diagram.drawio -m metrics.csv matches each metric (CSV key,value or JSON {key:value}) to a node by id or label and recolours it along a gradient (--palette heat|cool|warm, --reverse), optionally scaling node size (--size) and adding a legend. Post-processes any diagram; export as usual
scripts/seqlayout.py	The user wants a sequence diagram — describe participants + messages as JSON and the script computes all lifeline/activation/arrow geometry deterministically (no hand-placed coordinates, no Graphviz needed)
scripts/c4.py	The user wants a C4 model (System Context / Container / Component) — levels JSON in, one multi-page .drawio out with official C4 shapes/colors and click-to-drill-down links between levels
scripts/relabel.py	The user wants a language variant or bulk text swap of an existing .drawio (e.g. an EN diagram re-labelled in Chinese for a bilingual README) — relabel.py diagram.drawio --extract -o labels.json dumps every label as an identity JSON map; translate the values (keep the keys), then relabel.py diagram.drawio --map labels.json -o diagram_cn.drawio swaps them with layout/styles/ids untouched
scripts/restyle.py	The user wants to re-theme an EXISTING .drawio ("make this dark", "apply my corporate style to this diagram") — restyle.py diagram.drawio --preset <name> remaps every vertex fill/stroke to the preset palette by hue, applies font/extras (dark fontColor, edge color, background), and leaves layout, shapes, and edge routing untouched. Presets resolve like Step 0 (user dir, then built-ins)
scripts/edgeports.py	Edges stack on top of each other where they meet a shape — the usual swimlane/cross-functional complaint, and anywhere a node has several connections leaving the same side. edgeports.py diagram.drawio pins exitX/exitY+entryX/entryY: it picks the side of each node facing the other endpoint, then spreads that side's edges over evenly-spaced slots ordered by the far endpoint's position, so they keep their relative order instead of crossing. Resolves absolute coordinates through swimlane parents, skips ends you already pinned, and is idempotent. It is a port assigner, not a router — it separates lines at the shape boundary, it will not stop an edge crossing an unrelated shape mid-run (add waypoints for that)
scripts/validate.py	You generated a .drawio (especially via autolayout or for a large hand-placed diagram) and want a fast deterministic structural lint (dangling edges, dup/reserved ids, broken parents, overlaps) before the vision self-check. --score prints a readability score for comparing layout variants
scripts/raster2drawio.py	The user has an image of a diagram (whiteboard photo, legacy PNG, Visio screenshot) and wants an editable .drawio — read the image with your own vision, extract nodes/edges as JSON (schema + full workflow in references/derasterize.md), then raster2drawio.py graph.json -o out.drawio honours those coordinates/labels/shapes; nodes missing x/y fall back to autolayout.py placement
scripts/buildup.py	The user wants a diagram to build itself node-by-node as a video/GIF (a construction time-lapse of ONE static diagram — distinct from timelapse.py's git-history animation) — buildup.py diagram.drawio reveals cells in topological (dependency) order into a self-contained HTML player (play/pause/step/scrub); --gif also exports an animated GIF (needs Pillow). Needs the draw.io CLI
scripts/compress.py	The user wants an executive / boardroom summary of a big diagram — collapses clusters (pure-Python label propagation, no networkx) into one labeled node each with aggregated inter-cluster edges, emitting a 2-page .drawio (exec view + click-to-drill-down into the full original). Claude can rename clusters semantically afterward. Needs Graphviz dot
scripts/runbook.py	The user wants a flowchart/decision-tree .drawio turned into a click-through triage app (on-call runbook) — runbook.py flow.drawio reads the XML (no draw.io CLI needed) and emits a self-contained HTML runbook: current-step text, per-edge choice buttons, breadcrumb trail, Back/Restart, end-state on terminal nodes
scripts/prdiff.py	You're setting up automated PR diagram review in CI — for every .drawio changed between two git refs it renders base/head/diff PNGs and emits a Markdown report; ships with a composite GitHub Action (.github/actions/drawio-diff/) that posts a sticky PR comment. See references/pr-bot.md
scripts/tubemap.py	The user wants a metro / subway / tube map — a system, pipeline, or journey drawn as coloured transit lines with octilinear (H/V/45°) routing, white interchange circles, and station stops. Compose a metro JSON (lines = ordered stations on an integer grid, shared stations = interchanges), then tubemap.py metro.json -o metro.drawio. Stdlib-only; schema + the one grid rule in references/tubemap.md

Prerequisites

The draw.io desktop app must be installed and the CLI accessible:

macOS sandbox / sandbox isolation note (e.g., codex.app): In some sandboxed macOS environments, invoking the draw.io desktop CLI (even drawio --version) can crash the draw.io process or produce no output. If that happens, treat the CLI as unavailable in this sandbox isolation — do not keep retrying inside the sandbox. Prefer a non-sandboxed host environment (outside sandbox isolation) for any CLI export work, or use the browser fallback / XML-only outputs.

# macOS (Homebrew — recommended; CLI binary is `drawio`, not `draw.io`)
brew install --cask drawio
drawio --version

# macOS (full path if not in PATH)
/Applications/draw.io.app/Contents/MacOS/draw.io --version

# Windows
"C:\Program Files\draw.io\draw.io.exe" --version

# Linux
drawio --version

Install draw.io desktop if missing:

• macOS: brew install --cask drawio or download from https://github.com/jgraph/drawio-desktop/releases
• Windows: download installer from https://github.com/jgraph/drawio-desktop/releases
• Linux: download .deb/.rpm from https://github.com/jgraph/drawio-desktop/releases — do not use snap (AppArmor sandbox denies secrets/keyring on servers, causes crash)

Workflow

Before starting the workflow, assess whether the user's request is specific enough. If key details are missing, ask 1-3 focused questions:

• Diagram type — which preset? (ERD, UML, Sequence, Architecture, ML/DL, Flowchart, SysML, BPMN, Network, Swimlane, or general)
• Output format — PNG (default), SVG, PDF, or JPG?
• Output location — default is the user's working dir; honor any explicit path the user gives (e.g. "put it in ./artifacts/"). Don't ask if they didn't mention one.
• Scope/fidelity — how many components? Any specific technologies or labels?

Skip clarification if the request already specifies these details or is clearly simple (e.g., "draw a flowchart of X").

Step 0 — Resolve active preset. Determine which (if any) user-defined style preset applies to this generation.

• Scan the user's message for a phrase that clearly names a style preset: "use my <name> style", "with my <name> style", "in <name> mode", "in the style of <name>". A bare with <name> does not count — "draw a diagram with redis" names a component, not a style. If a clear match is found → active preset = <name>.
• Else, check ~/.drawio-skill/styles/ for any file with "default": true. If found → active preset = that one.
• Else → no preset active; fall through to the built-in color/shape/edge conventions for the rest of the workflow.

Load the preset JSON from ~/.drawio-skill/styles/<name>.json, falling back to <this-skill-dir>/styles/built-in/<name>.json. If the named preset exists in neither location, tell the user the name is unknown, list the available presets (user dir + built-in), and stop — do not silently fall back to defaults.

When a preset loads successfully, mention it in the first line of the reply: "Using preset <name> (confidence: <level>)." See references/style-presets.md → "Applying a preset" for how the preset changes color/shape/edge/font decisions.