Excalidraw Skill logo

Excalidraw Skill

CommunityPopular
yctimlin
excalidraw-skill

Excalidraw canvas toolkit for creating, editing, and refining diagrams on a live canvas. Use when an agent needs to (1) draw or lay out diagrams, (2) iteratively refine them by describing the scene and screenshotting its own work, (3) export/import .excalidraw files or PNG/SVG images, (4) save/restore canvas snapshots, (5) convert Mermaid to Excalidraw, or (6) perform element-level CRUD, alignment, distribution, grouping, duplication, and locking. Primary interface is the bundled CLI (npx -y mcp-excalidraw-server <command>) which auto-starts the canvas server; MCP tools and a REST API are equivalent alternatives.

Overview

Publisheryctimlin
Repositorymcp_excalidraw
Skill nameexcalidraw-skill
Stars
2.4K
Forks
272
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by yctimlin on GitHub. Read the source before you install it.

Installation

Install the Excalidraw Skill AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/yctimlin/mcp_excalidraw.git /tmp/mcp_excalidraw
mkdir -p .claude/skills
cp -r /tmp/mcp_excalidraw/skills/excalidraw-skill .claude/skills/excalidraw-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Excalidraw Skill in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Excalidraw Skill on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Excalidraw Skill is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Excalidraw Skill

Step 0: Pick an Interface

Three interfaces drive the same live canvas. Pick the first one that applies:

  1. MCP tools — if excalidraw/* tools (e.g. batch_create_elements) are in your tool list, prefer them: results land directly in your context, and screenshots come back as images without touching disk.
  2. CLI (default when no MCP tools are present):
    bash
    npx -y mcp-excalidraw-server <command>
    No setup needed — any canvas-touching command auto-starts the canvas server on http://127.0.0.1:3000 (first npx run downloads the package). If the CLI is installed globally (npm i -g mcp-excalidraw-server), the shorter alias excalidraw-canvas <command> works too.
  3. REST API (last resort, e.g. from application code): HTTP endpoints on http://127.0.0.1:3000 — see references/cheatsheet.md for payloads. The server must already be running.

The canvas URL comes from EXPRESS_SERVER_URL (default http://127.0.0.1:3000). Remind the user to open that URL in a browser — screenshots, image export, mermaid conversion, and viewport control need an open tab (CLI exits with code 4 when it's missing).

CLI Quick Reference

Results are JSON on stdout — except describe (plain text) and raw-content output when --out is omitted (export scene JSON, screenshot --format svg). Diagnostics on stderr. Exit codes: 0 ok, 1 error, 2 usage, 3 canvas unreachable, 4 browser tab required.

TaskCommand
Start / stop / inspect serverstart, stop, status
Create elements (batch)add elements.json or echo '[...]' | add or add --one '{...}'
Multi-op patch in one callapply patch.json{"create":[...],"update":[{"id":"a","set":{...}}],"delete":[...]}
Read one / query manyget <id>, query [--type t] [--bbox x0,y0,x1,y1] [--filter k=v] [--filter-json '{...}']
Update / deleteupdate <id> --set '{...}', delete <id> [...]
Understand the scenedescribe (plain-text summary: ids, positions, labels, connections)
See the scenescreenshot [--out f.png] (PNG without --out → temp file path in JSON; SVG without --out → raw SVG)
Layout operationsarrange align|distribute|group|ungroup|lock|unlock|duplicate --ids a,b,c [--to left|horizontal|...]
Scene filesexport [--out scene.excalidraw], `import [scene.excalidraw
Mermaid → canvas`mermaid [diagram.mmd
Snapshotssnapshot save|list|restore <name>
Share linkshare (encrypted upload → excalidraw.com URL)
Wipe canvasclear --yes
Install / upgrade this skillinstall-skill --dir <skills-root> (agent chooses project/global root)

Element Format (CLI and MCP)

The CLI and MCP tools accept the same agent-friendly format and normalize it automatically:

  • Labels: put "text": "My Label" on any shape — converted to Excalidraw's bound-label format for you.
  • Arrow binding: "startElementId": "a" / "endElementId": "b" — arrows auto-route to element edges.
  • fontFamily: pass a string name ("helvetica", "cascadia", "excalifont", ...) or string number "1""8".
  • points: both [[x,y], ...] tuples and [{"x":..,"y":..}] objects are accepted.
  • Patch updates: in apply, update entries can use either direct fields ({"id":"a","x":120}) or a set object ({"id":"a","set":{"x":120}}). Do not mix both forms in one update entry.

Raw REST is stricter: labels must be "label": {"text": "..."}, bindings must be "start": {"id": "..."} / "end": {"id": "..."}. Only worry about this when POSTing to the API directly.


Coordinate System

The canvas uses a 2D coordinate grid: (0, 0) is the origin, x increases rightward, y increases downward. Plan your layout before writing any JSON.

General spacing guidelines:

  • Vertical spacing between tiers: 80–120px (enough that arrows don't crowd labels)
  • Horizontal spacing between siblings: 40–60px minimum; give labeled arrows 120px+
  • Shape width: max(160, labelCharCount * 12) to keep the label on one line
  • Shape height: 60px single-line, 80px two-line labels
  • Background/zone padding: 50px on all sides around contained elements

Styling for a professional look:

  • "fillStyle": "solid" on shapes gives crisp flat fills — the default is a sketchy hachure pattern
  • Pair pastel backgroundColor fills with their darker strokeColor (palette in the cheatsheet)
  • "strokeStyle": "dashed" on zone borders and async arrows reads as "boundary / background"

Layout Anti-Patterns (Critical for Complex Diagrams)

These are the most common mistakes that produce unreadable diagrams. Avoid all of them.

1. Do NOT use label.text (or text) on large background zone rectangles

When you put a label on a background rectangle, Excalidraw creates a bound text element centered in the middle of that shape — right where your service boxes will be placed. The text overlaps everything inside the zone and cannot be repositioned.

Wrong:

json
{"id": "vpc-zone", "type": "rectangle", "x": 50, "y": 50, "width": 800, "height": 400, "text": "VPC (10.0.0.0/16)"}

Right — use a free-standing text element anchored at the top of the zone:

json
{"id": "vpc-zone", "type": "rectangle", "x": 50, "y": 50, "width": 800, "height": 400, "backgroundColor": "#e3f2fd"},
{"id": "vpc-label", "type": "text", "x": 70, "y": 60, "width": 300, "height": 30, "text": "VPC (10.0.0.0/16)", "fontSize": 18}

The free-standing text element sits at the top corner of the zone and doesn't interfere with elements placed inside.

2. Avoid cross-zone arrows in complex diagrams

An arrow from an element in one layout zone to an element in a distant zone will draw a long diagonal line crossing through everything in between. In a multi-zone infra diagram this produces an unreadable tangle of spaghetti.

Design rule: Keep arrows within the same zone or tier. To show cross-zone relationships, use annotation text or separate the zones so their edges are adjacent (no elements between them), and route the arrow along the edge.

If you must connect across zones, use an elbowed arrow that travels along the perimeter — never through the middle of another zone.

3. Use arrow labels sparingly

Arrow labels are placed at the midpoint of the arrow. On short arrows, they overlap the shapes at both ends. On crowded diagrams, they collide with nearby elements.

  • Only add an arrow label when the relationship name is genuinely essential (e.g., protocol, port number, data direction).
  • If you're adding a label to every arrow, reconsider — it usually adds visual noise, not clarity.
  • Keep arrow labels to ≤ 12 characters. Prefer omitting them entirely on dense diagrams.

Quality: Why It Matters (and How to Check)

Excalidraw diagrams are visual communication. If text is cut off, elements overlap, or arrows cross through unrelated shapes, the diagram becomes confusing and unprofessional — it defeats the whole purpose of drawing it. So after every batch of elements, verify before adding more.

Quality Checklist

After each add / apply / batch_create_elements, take a screenshot and check:

  1. Text truncation — Is all label text fully visible? Truncated text means the shape is too small. Increase width and/or height.
  2. Overlap — Do any shapes share the same space? Background zones must fully contain children with padding.
  3. Arrow crossing — Do arrows cut through unrelated elements? If yes, route them around using curved or elbowed arrows (see Arrow Routing below).
  4. Arrow-label overlap — Arrow labels sit at the midpoint. If they overlap a shape, shorten the label or adjust the arrow path.
  5. Spacing — At least 40px gap between elements. Cramped layouts are hard to read.
  6. Readability — Font size ≥ 16 for body text, ≥ 20 for titles.
  7. Zone label placement — If you used text/label.text on a background zone rectangle, the zone label will be centered in the middle of the zone, overlapping everything inside. Fix: delete the bound text element and add a free-standing text element at the top of the zone instead (see Layout Anti-Patterns above).

If you find any issue: stop, fix it, re-screenshot, then continue. Say "I see [issue], fixing it" rather than glossing over problems. Only proceed once all checks pass.


Workflow: Drawing a New Diagram

Mermaid vs. Direct Creation — Which to Use?

Use mermaid / create_from_mermaid when: the user already has a Mermaid diagram, or the structure maps cleanly to a flowchart/sequence/ER diagram with standard Mermaid syntax. It's fast and handles conversion automatically, though you get less control over exact layout.

Create elements directly when: you need precise layout control, the diagram type doesn't map to Mermaid well (e.g., custom architecture, annotated cloud diagrams), or you want elements positioned in a specific coordinate grid.

Steps (CLI shown; MCP tools are 1:1 — see cheatsheet)

  1. Plan your coordinate grid — map out tiers and x-positions before writing JSON. (MCP mode: call read_diagram_guide for colors/sizing; the same guidance lives in references/cheatsheet.md.)
  2. Optional fresh start: npx -y mcp-excalidraw-server clear --yes
  3. Create shapes and arrows in one call. Custom id fields (e.g. "id": "auth-svc") make later updates easy:
    bash
    npx -y mcp-excalidraw-server add - <<'EOF'
    [
      {"id": "lb", "type": "rectangle", "x": 300, "y": 50, "width": 180, "height": 60, "text": "Load Balancer"},
      {"id": "svc-a", "type": "rectangle", "x": 100, "y": 200, "width": 160, "height": 60, "text": "Web Server 1"},
      {"id": "svc-b", "type": "rectangle", "x": 450, "y": 200, "width": 160, "height": 60, "text": "Web Server 2"},
      {"id": "db", "type": "rectangle", "x": 275, "y": 350, "width": 210, "height": 60, "text": "PostgreSQL"},
      {"type": "arrow", "x": 0, "y": 0, "startElementId": "lb", "endElementId": "svc-a"},
      {"type": "arrow", "x": 0, "y": 0, "startElementId": "lb", "endElementId": "svc-b"},
      {"type": "arrow", "x": 0, "y": 0, "startElementId": "svc-a", "endElementId": "db"},
      {"type": "arrow", "x": 0, "y": 0, "startElementId": "svc-b", "endElementId": "db"}
    ]
    EOF
    (The - positional is optional — with no file argument, add reads stdin.)
  4. Set shape widths using max(160, labelLength * 12).
  5. screenshot → view the file → run the Quality Checklist → fix issues before the next batch.

Arrow Routing — Avoid Overlaps

Straight arrows can cross through elements in complex diagrams. Use curved or elbowed arrows when needed:

Curved arrows (smooth arc over obstacles):

json
{
  "type": "arrow", "x": 100, "y": 100,
  "points": [[0, 0], [50, -40], [200, 0]],
  "roundness": {"type": 2}
}

The intermediate waypoint [50, -40] lifts the arrow upward. roundness: {type: 2} makes it smooth.

Elbowed arrows (right-angle / L-shaped routing):

json
{
  "type": "arrow", "x": 100, "y": 100,
  "points": [[0, 0], [0, -50], [200, -50], [200, 0]],
  "elbowed": true
}

When to use which:

  • Fan-out (one source → many targets): curved arrows with waypoints spread to avoid overlapping
  • Cross-lane (connecting to side panels): elbowed arrows that go up, then across, then down
  • Long horizontal connections: curved arrows with a slight vertical offset

Rule: If an arrow would pass through an unrelated shape, add a waypoint to route around it.


Workflow: Iterative Refinement

Pairing describe with screenshot is what makes this skill powerful.

  • describe (describe_scene in MCP) → structured text: element IDs, types, positions, labels, connections. Use it to know what's on the canvas before making programmatic updates (find IDs, understand bounding boxes).
  • screenshot (get_canvas_screenshot in MCP) → PNG of the actual rendered canvas. Use it for visual quality verification — it shows exactly what the user sees, including truncation, overlap, and arrow routing. The CLI prints the saved file path as JSON; read/view that file.

Feedback loop:

add elements
  → screenshot → view → "text truncated on auth-svc"
  → update auth-svc --set '{"width": 220}' → screenshot → "overlap between auth-svc and rate-limiter"
  → update rate-limiter --set '{"x": 520}' → screenshot → "all checks pass"
  → proceed

Workflow: Refine an Existing Diagram

  1. describe to understand current state — note element IDs and positions.
  2. Identify elements by id or label text (not by x/y coordinates — they change).
  3. update <id> --set '{...}' to resize/recolor/move; delete <id> to remove; or bundle everything in one apply patch. Bound arrows re-route automatically when you move or resize their endpoints — no need to delete and recreate them.
  4. screenshot to confirm the change looks right.
  5. If updates fail: check the ID exists with get <id>; unlock with arrange unlock --ids <id> if locked.

Workflow: Mermaid Conversion

bash
echo 'graph TD
  A[Client] --> B[API]
  B --> C[(DB)]' | npx -y mcp-excalidraw-server mermaid

Requires an open browser tab (conversion runs in the frontend; exit code 4 tells you to open the canvas URL). Afterwards screenshot to verify layout. If the auto-layout is poor (nodes crowded, edges crossing), find problem elements with describe and reposition them with update.

Workflow: File I/O

  • Export scene: export --out diagram.excalidraw (no --out → JSON to stdout)
  • Import scene: import diagram.excalidraw (append) or import diagram.excalidraw --replace
  • Image: screenshot --out diagram.png / screenshot --format svg --out diagram.svg (browser tab required)
  • Share link: share — encrypts the scene and returns a shareable excalidraw.com URL

This is how diagrams live in a repo: commit the .excalidraw file, and re-import + edit + export it when the architecture changes.

Obsidian vaults: use .excalidraw.md

Check the destination before writing: if any ancestor directory contains .obsidian/, it is an Obsidian vault. A raw .excalidraw file there opens in the Excalidraw plugin only in compatibility mode ("Convert to new format" warning), gets no block references or vault-wide search, and default Obsidian Sync skips non-.md files. Give the export a .excalidraw.md extension and the CLI writes the plugin's native format automatically:

bash
npx -y mcp-excalidraw-server export --out "$VAULT/diagrams/system-map.excalidraw.md"   # .md → Obsidian format (or force with --format obsidian)
npx -y mcp-excalidraw-server import "$VAULT/diagrams/system-map.excalidraw.md" --replace  # reads both plain and compressed Drawing blocks

Round-trips are safe: text-element block references follow the plugin's own id rules, so re-importing, editing, and re-exporting the same file keeps links from other notes intact.

Workflow: Snapshots

  1. snapshot save <name> before risky changes.
  2. Make changes, evaluate with describe / screenshot.
  3. snapshot restore <name> to roll back if needed. snapshot list shows what's saved.

Workflow: Duplication

arrange duplicate --ids a,b --offset 40,40 (default offset 20,20). Useful for repeated patterns or copying layouts.

Error Recovery

  • Exit code 3 (canvas unreachable)? Auto-start is disabled (EXCALIDRAW_NO_AUTOSTART=1) or a non-loopback EXPRESS_SERVER_URL is set. Run start explicitly or fix the env.
  • Exit code 4 (browser required)? Open http://127.0.0.1:3000 in a browser, then retry — screenshots, image export, viewport, and mermaid conversion render in the frontend.
  • Elements not appearing? Check describe — they may be off-screen. In MCP mode, use set_viewport with scrollToContent: true, or scrollToElementIds plus optional viewportZoomFactor to focus on a specific subgraph; in a browser, press the zoom-to-fit button.
  • Arrow not connecting? Verify element IDs with get <id>. Make sure startElementId/endElementId match existing element IDs.
  • Canvas in a bad state? snapshot save first, then clear --yes and rebuild. Or snapshot restore to go back.
  • Element won't update? It may be locked — arrange unlock --ids <id> first.
  • Duplicate text elements / element count doubling? The frontend auto-sync timer periodically writes the full Excalidraw scene back to the server. Excalidraw internally generates a bound text element for every shape with a label; clearing and re-sending elements can re-inject cached bound texts. Clean up: query --type text to find elements with a containerId, delete the unwanted ones, wait a few seconds for auto-sync to settle. The safest prevention: never put labels on background zone rectangles — use free-standing text elements.

References

  • references/cheatsheet.md: full CLI reference, the 26 MCP tools, REST API endpoints + payload shapes, and the diagram design guide (colors, sizing).

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Excalidraw Skill AI skill do?

Excalidraw canvas toolkit for creating, editing, and refining diagrams on a live canvas. Use when an agent needs to (1) draw or lay out diagrams, (2) iteratively refine them by describing the scene and screenshotting its own work, (3) export/import .excalidraw files or PNG/SVG images, (4) save/restore canvas snapshots, (5) convert Mermaid to Excalidraw, or (6) perform element-level CRUD, alignment, distribution, grouping, duplication, and locking. Primary interface is the bundled CLI (npx -y mcp-excalidraw-server <command>) which auto-starts the canvas server; MCP tools and a REST API are e...

Why use Excalidraw Skill on TypingMind?

Because you install it once and use it with any model. Excalidraw Skill is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Excalidraw Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yctimlin/mcp_excalidraw/tree/main/skills/excalidraw-skill. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Excalidraw Skill?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Excalidraw Skill?

As many as you like. As long as a model supports skills, you can use Excalidraw Skill with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Excalidraw Skill AI skill free?

Yes. It is published on GitHub by yctimlin under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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