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Generate polished .drawio diagrams — architecture, UML, ERD, flowcharts, ML/DL model figures, network topology, mind maps, and any visualization.
Passed 17 of 20 test cases with the skill, and 6 of 20 without it.
and 10 more in the full report
13 fixed7 passed either way3 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
I am creating a draw.io diagram featuring an architecture that calls Claude and OpenAI models. Draw.io doesn't have standard shapes for LLM logos. What helper script in the skill set should be used to retrieve the icon styles?
| Checked | Without skill | With skill |
|---|---|---|
| Uses or references aiicons.py to look up LLM brand icon styles. | Missed | Passed |
The instructions your model reads when the skill loads.
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.
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:
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/diagram-types.md | The user names a specific diagram type (ERD, UML class, sequence, architecture, ML/DL, flowchart). Read in full when drawing sequence diagrams with activation bars, multi-scene layouts, or cross-layer specific-to-specific call arrows — these are non-obvious geometry rules that prevent bar/arrow overlap and z-order glitches |
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/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 |
test cases passed, vs 6 / 20 without
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