drawio-skill

Agents365-ai/drawio-skill · Agent Skill

建立、編輯和同步 draw.io 圖表。適用於架構、ERD、UML、BPMN 等圖。將程式碼轉換為圖表。

前往安裝 ↓

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發布者Agents365-ai社群
儲存庫Agents365-ai/drawio-skill ↗
技能資料夾drawio-skill
星9,126
附帶檔案1
授權MIT
最近更新2026年9月2日
連結技能原始碼 ↗ · 儲存庫 ↗

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我們在技能檔案中發現的內容。詳細資訊需訂閱。

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安裝

技能就是一個含 SKILL.md 的資料夾。選擇你的代理,在專案根目錄的終端機(macOS、Linux 或 Windows 的 Git Bash)執行指令。

把提示貼到 Claude、Codex 或其他助理:它會自行檢查並安裝技能。

Install the “drawio-skill” skill from mozgi.io (https://mozgi.io/skills/drawio-skill/) for me.

1. Download the archive: https://mozgi.io/skills/drawio-skill/download
   If it fails, take the skill folder from the source: https://github.com/Agents365-ai/drawio-skill/tree/main/skills/drawio-skill
2. Read SKILL.md and the other files. Check the skill is safe: no hidden commands, no sending data elsewhere, no scripts doing something other than described. If anything looks suspicious, stop and tell me.
3. Put the “drawio-skill” folder into your agent's skills folder: .claude/skills/ for Claude Code, .agents/skills/ for Codex, .cursor/skills/ for Cursor, .gemini/skills/ for Gemini CLI. Inside the project if we are in one, otherwise in the home folder (~/.claude/skills/ etc.).
4. Make sure <skills folder>/drawio-skill/SKILL.md exists.
5. Briefly tell me what this skill does and offer to try it on my task.

If you cannot do a step yourself, tell me what to click or type.

技能檔案

1 個檔案 下載 ZIP

安裝前請先檢視 SKILL.md 與相關檔案。點擊檔案即可預覽。

SKILL.md 內容

作者原文 · 唯讀

Draw.io Architecture Studio

Produce editable .drawio artifacts, not flattened pictures. The preferred

entrypoint is scripts/diagramctl.py, which unifies generation, incremental

sync, multi-view projection, semantic queries/tests/reviews, failure analysis,

and accessible publishing over a shared Diagram IR.

Choose the workflow

| Request | Route |

| --- | --- |

| Natural-language diagram with precise styling | Read references/diagram-types.md, then references/xml-authoring.md and author XML |

| Standard flowchart/mindmap/gantt/timeline/etc. with no special styling | If draw.io >=30, read references/mermaid-authoring.md and convert Mermaid to native .drawio |

| Large graph (~15+ nodes) that needs automatic layout | Use autolayout.py; read references/autolayout.md before passing any --layout value |

| Code, Terraform, K8s, compose, SQL, OpenAPI, AsyncAPI, or CI source | Use diagramctl.py build; read references/diagram-ir.md |

| Protocol Buffers schema (.proto) | Use protoimports.py or diagramctl.py build; read references/toolbox.md |

| GraphQL SDL schema (.graphql/.gql) or introspection JSON | Use graphqlerd.py or diagramctl.py build; read references/toolbox.md |

| Running cluster/stack/cloud (actual state, not declared config) | Read references/live-infra.md, then use tfstate.py, dockerimports.py, or k8simports.py - |

| Update a generated diagram without losing manual layout | Use diagramctl.py sync; read references/diagram-ir.md |

| Executive/system/deployment/data-flow/security views | Use diagramctl.py views; read references/diagram-ir.md |

| Query, architecture policy, review, what-if, or guided walkthrough | Read references/semantic-workflows.md |

| MCP host (Claude Desktop, Cursor, VS Code, Codex) should call these workflows | Register scripts/diagramctl_mcp.py; read references/mcp.md |

| Prompt phrasing for a diagram type or semantic workflow | Read references/cookbook.md |

| Enforce architecture rules or visual diffs in GitHub Actions CI | Read references/ci-gate.md |

| Rendered before/after/diff images as a PR review comment | Use prdiff.py; read references/pr-bot.md |

| Existing .drawio to HTML/PPTX/Mermaid/Markdown/animation/runbook | Read references/toolbox.md; diagramctl.py transform exposes the existing tools |

| Pipeline, journey, or subsystem map drawn as a metro/subway map | Use tubemap.py; read references/tubemap.md |

| Shape, cloud/vendor, AI, or Databricks icon | Read references/shapes.md or references/databricks.md; never guess shape names |

| Learn/apply/manage a visual style | Read references/style-presets.md |

| Extract a reusable style from an existing diagram or theme | Read references/style-extraction.md |

| Existing image to editable diagram (screenshot, whiteboard photo, legacy PNG) | Read references/derasterize.md |

| Export/platform problem | Read references/troubleshooting.md; for access/network questions read references/security.md |

Unified CLI

Run from this skill directory, or replace scripts/ with the absolute path to

this skill's scripts directory:

python3 scripts/diagramctl.py doctor
python3 scripts/diagramctl.py build model.json --from ir -o architecture.drawio
python3 scripts/diagramctl.py build ./infra --from terraform --group \
  --ir-output architecture.ir.json -o architecture.drawio
python3 scripts/diagramctl.py sync architecture.drawio ./infra --from terraform \
  -o architecture.next.drawio
python3 scripts/diagramctl.py views architecture.ir.json \
  --views executive,system,deployment,dataflow,security -o views.drawio
python3 scripts/diagramctl.py test architecture.drawio --rules policy.yml
python3 scripts/diagramctl.py review architecture.drawio -o review.md
python3 scripts/diagramctl.py query architecture.drawio --from internet --to orders-db
python3 scripts/diagramctl.py whatif architecture.ir.json --fail kafka \
  --drawio kafka-failure.drawio -o impact.json
python3 scripts/diagramctl.py story architecture.ir.json -o walkthrough.html

doctor does not launch GUI tools unless --probe is passed. Core semantic

commands are offline and stdlib-only.

Creation workflow

1. Infer the diagram type, audience, scope, output format, and location from the

request. Ask only when a missing choice materially changes the result;

default to PNG plus .drawio in the working directory.

2. Select the authoring route from the table above. For a data-backed diagram,

prefer Diagram IR and preserve provenance. For a large graph, use an importer

or autolayout.py; do not hand-place more than roughly fifteen nodes.

3. Resolve an explicitly named style preset, or the user's default preset, as

documented in references/style-presets.md. Structural diagram conventions

and visual presets compose; they do not replace each other.

4. Generate the .drawio, then run structural validation:

```bash

python3 scripts/validate.py diagram.drawio --score

```

When semantic metadata or an architecture policy is in scope, also run

diagramctl.py test. Do not present inferred semantic findings as verified

runtime facts.

5. Export a draft PNG without embedded XML and inspect it visually. Fix obvious

overlap, clipping, disconnected edges, edge-through-node routing, stacked

edges, and unreadable labels. Stop automatic vision repair after two rounds.

6. Show the draft and apply targeted edits. Preserve existing geometry for

local changes. Use sync for source-backed changes and write a reviewable

output; use --prune only when deletion was requested.

7. After approval, create final requested formats and report both editable

source and export paths.

Export invariants

Resolve the available binary once (drawio, draw.io, the macOS app path, or

the Windows executable) and use that exact binary for the run.

# Draft for visual inspection: never use -e here
drawio -x -f png --width 2000 -o diagram.png diagram.drawio

# Final editable PNG
drawio -x -f png -e -s 2 -o diagram.drawio.png diagram.drawio
python3 scripts/repair_png.py diagram.drawio.png

# Final editable SVG/PDF
drawio -x -f svg -e --embed-svg-images -o diagram.svg diagram.drawio
drawio -x -f pdf -e -o diagram.pdf diagram.drawio

Do not combine --width and -s. Embedded PNG exports require

repair_png.py; draft PNGs used by vision must not use -e. On Linux headless,

follow references/troubleshooting.md rather than improvising Electron flags.

If the CLI crashes in a macOS sandbox, try one permitted escalated run, then use

encode_drawio_url.py or deliver XML; do not repeatedly launch it.

Editing and identity

  • Use stable semantic IDs and never reuse reserved IDs 0 or 1.
  • Every edge requires <mxGeometry relative="1" as="geometry"/>.
  • For a local edit, change the matching cell only; for a global direction

change, regenerate/re-layout the page.

  • Keep provenance, data-model-id, semantic properties, manual geometry, and

manual styles intact unless the user requests otherwise.

  • When reconciling, retain removals as reviewable faded elements by default.
  • For edges stacked at a boundary, run edgeports.py; add waypoints when an

edge still crosses an unrelated shape. There is no CLI-only edge rerouter

that preserves node positions.

Quality and trust

An attractive diagram can still be wrong. Prefer source-backed relationships,

show provenance where useful, distinguish exact extraction from AI inference,

and keep architecture review findings framed as prompts. Story HTML must remain

self-contained, keyboard usable, and include a text alternative. Never include

secrets in node properties or provenance because they are embedded in outputs.

For all focused scripts and composition patterns, read references/toolbox.md;

load only the task-specific reference needed for the current request.

常見問題

drawio-skill 技能有什麼用途?

建立、編輯和同步 draw.io 圖表。適用於架構、ERD、UML、BPMN 等圖。將程式碼轉換為圖表。

如何安裝 drawio-skill?

打開本頁的「安裝」區塊並選擇你的代理 — Claude Code、Codex、Cursor 或 Gemini CLI:那裡有把技能資料夾複製到正確位置的現成指令。也可以複製「透過助理」分頁中的提示,讓助理自行檢查並安裝技能。

drawio-skill 適用哪些 AI 模型?

技能是純 Markdown 指示(Agent Skills 格式),因此 drawio-skill 適用任何讀取 SKILL.md 的代理:Claude Code、Codex、Cursor、Gemini CLI、GitHub Copilot、OpenCode 等。只有在任務符合技能描述時,模型才會載入指示。

drawio-skill 是免費的嗎?

此技能由 Agents365-ai 公開發布,採用 MIT 授權。技能本身免費 — 你只需向 AI 供應商支付實際使用的 token 費用。

安裝技能安全嗎?

技能是代理會遵循的指示,安裝前請閱讀 SKILL.md 及相關檔案。技能資料夾中的腳本只有在代理執行時才會運行 — 留意它的動作,不要授予多餘權限。

技能和 MCP 伺服器或外掛有何不同?

MCP 伺服器或外掛為模型提供新工具 — 會執行並回傳結果的程式碼。技能提供的是知識與流程:如何處理任務、要遵循哪些步驟、好的成果長什麼樣子。它不需要伺服器或 API 金鑰。

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