Excalidraw Diagram

Excalidraw Diagram Creator

Generate .excalidraw JSON files that argue visually, not just display information.

Setup: If the user asks you to set up this skill (renderer, dependencies, etc.), see README.md for instructions.

Provenance: The design methodology began as a fork of coleam00/excalidraw-diagram-skill. The render pipeline was rebuilt around Excalidraw (@excalidraw/excalidraw, MIT): the engine is fetched from a pinned, sha256-verified GitHub Release on first render, cached under references/vendor/, and served locally from then on — offline after that one-time fetch, like playwright install chromium. The icon-library ingestion approach (split a .excalidrawlib into per-icon files + an index, then place deterministically) is credited to github/awesome-copilot (MIT); the scripts here are an independent implementation. The MIT license on this skill covers the skill content; the vendored Excalidraw bundle and fonts remain under their own (MIT / respective) licenses, and any user-supplied icon libraries remain under theirs.

Customization

All colors and brand-specific styles live in one file: references/color-palette.md. Read it before generating any diagram and use it as the single source of truth for all color choices — shape fills, strokes, text colors, evidence artifact backgrounds, everything.

To make this skill produce diagrams in your own brand style, edit color-palette.md. Everything else in this file is universal design methodology and Excalidraw best practices.

Core Philosophy

Diagrams should ARGUE, not DISPLAY.

A diagram isn't formatted text. It's a visual argument that shows relationships, causality, and flow that words alone can't express. The shape should BE the meaning.

The Necessity Test — ask this first, because it can end the job: would a table or a paragraph do the same work? If yes, write that instead and say why. A list of items with no relationships between them is a table. A sequence with no branching is a numbered list. Drawing those wastes the reader's attention on shapes that carry no argument, and it wastes yours. Declining to draw is a valid deliverable.

The Isomorphism Test: If you removed all text, would the structure alone communicate the concept? If not, redesign.

The Education Test: Could someone learn something concrete from this diagram, or does it just label boxes? A good diagram teaches—it shows actual formats, real event names, concrete examples.

Depth Assessment (Do This First)

Before designing, determine what level of detail this diagram needs:

Simple/Conceptual Diagrams

Use abstract shapes when:

• Explaining a mental model or philosophy
• The audience doesn't need technical specifics
• The concept IS the abstraction (e.g., "separation of concerns")

Comprehensive/Technical Diagrams

Use concrete examples when:

• Diagramming a real system, protocol, or architecture
• The diagram will be used to teach or explain (e.g., YouTube video)
• The audience needs to understand what things actually look like
• You're showing how multiple technologies integrate

For technical diagrams, you MUST include evidence artifacts (see below).

Research Mandate (For Technical Diagrams)

Before drawing anything technical, research the actual specifications.

If you're diagramming a protocol, API, or framework:

1. Look up the actual JSON/data formats
2. Find the real event names, method names, or API endpoints
3. Understand how the pieces actually connect
4. Use real terminology, not generic placeholders

Bad: "Protocol" → "Frontend" Good: "AG-UI streams events (RUN_STARTED, STATE_DELTA, A2UI_UPDATE)" → "CopilotKit renders via createA2UIMessageRenderer()"

Research makes diagrams accurate AND educational.

Evidence Artifacts

Evidence artifacts are concrete examples that prove your diagram is accurate and help viewers learn. Include them in technical diagrams.

Types of evidence artifacts (choose what's relevant to your diagram):

Example: For a diagram about a streaming protocol, you might show:

• The actual event names from the spec (not just "Event 1", "Event 2")
• A code snippet showing how to connect
• What the streamed data actually looks like

Example: For a diagram about a data transformation pipeline:

• Show sample input data (actual format, not "Input")
• Show sample output data (actual format, not "Output")
• Show intermediate states if relevant

The key principle: show what things actually look like, not just what they're called.

Multi-Zoom Architecture

Comprehensive diagrams operate at multiple zoom levels simultaneously. Think of it like a map that shows both the country borders AND the street names.

Level 1: Summary Flow

A simplified overview showing the full pipeline or process at a glance. Often placed at the top or bottom of the diagram.

Example: Input → Processing → Output or Client → Server → Database

Level 2: Section Boundaries

Labeled regions that group related components. These create visual "rooms" that help viewers understand what belongs together.

Example: Grouping by responsibility (Backend / Frontend), by phase (Setup / Execution / Cleanup), or by team (User / System / External)

Level 3: Detail Inside Sections

Evidence artifacts, code snippets, and concrete examples within each section. This is where the educational value lives.

Example: Inside a "Backend" section, you might show the actual API response format, not just a box labeled "API Response"

For comprehensive diagrams, aim to include all three levels. The summary gives context, the sections organize, and the details teach.

Bad vs Good

Simple vs Comprehensive (Know Which You Need)

Simple diagrams are fine for abstract concepts, quick overviews, or when the audience already knows the details. Comprehensive diagrams are needed for technical architectures, tutorials, educational content, or when you want the diagram itself to teach.

Container vs. Free-Floating Text

Not every piece of text needs a shape around it. Default to free-floating text. Add containers only when they serve a purpose.

Typography as hierarchy: Use font size, weight, and color to create visual hierarchy without boxes. A 28px title doesn't need a rectangle around it.

The container test: For each boxed element, ask "Would this work as free-floating text?" If yes, remove the container.

Design Process (Do This BEFORE Generating JSON)

Step 0: Assess Depth Required

Before anything else, determine if this needs to be:

• Simple/Conceptual: Abstract shapes, labels, relationships (mental models, philosophies)
• Comprehensive/Technical: Concrete examples, code snippets, real data (systems, architectures, tutorials)

If comprehensive: Do research first. Look up actual specs, formats, event names, APIs.

Step 1: Understand Deeply

Read the content. For each concept, ask:

• What does this concept DO? (not what IS it)
• What relationships exist between concepts?
• What's the core transformation or flow?
• What would someone need to SEE to understand this? (not just read about)

Step 2: Map Concepts to Patterns

For each concept, find the visual pattern that mirrors its behavior:

Step 3: Ensure Variety

For multi-concept diagrams: each major concept must use a different visual pattern. No uniform cards or grids.

Step 4: Sketch the Flow

Before JSON, mentally trace how the eye moves through the diagram. There should be a clear visual story.

Step 5: Generate JSON

Only now create the Excalidraw elements. See below for how to handle large diagrams.

Before you start, skim references/examples/ — worked diagrams (JSON + rendered PNG) that show this methodology in practice. Read the one closest to what you're drawing; it's faster to imitate good moves than to derive them.

Step 6: Render & Validate (MANDATORY)

After generating the JSON, you MUST run the render-view-fix loop until the diagram looks right. This is not optional — see the Render & Validate section below for the full process.

Large / Comprehensive Diagram Strategy

For comprehensive or technical diagrams, you MUST build the JSON one section at a time. Do NOT attempt to generate the entire file in a single pass. This is a hard constraint — Claude Code has a ~32,000 token output limit per response, and a comprehensive diagram easily exceeds that in one shot. Even if it didn't, generating everything at once leads to worse quality. Section-by-section is better in every way.

The Section-by-Section Workflow

Phase 1: Build each section

1. Create the base file with the JSON wrapper (type, version, appState, files) and the first section of elements.
2. Add one section per edit. Each section gets its own dedicated pass — take your time with it. Think carefully about the layout, spacing, and how this section connects to what's already there.
3. Use descriptive string IDs (e.g., "trigger_rect", "arrow_fan_left") so cross-section references are readable.
4. Namespace seeds by section (e.g., section 1 uses 100xxx, section 2 uses 200xxx) to avoid collisions.
5. Update cross-section bindings as you go. When a new section's element needs to bind to an element from a previous section (e.g., an arrow connecting sections), edit the earlier element's boundElements array at the same time.

Phase 2: Review the whole

After all sections are in place, read through the complete JSON and check:

• Are cross-section arrows bound correctly on both ends?
• Is the overall spacing balanced, or are some sections cramped while others have too much whitespace?
• Do IDs and bindings all reference elements that actually exist?

Fix any alignment or binding issues before rendering.

Phase 3: Render & validate

Now run the render-view-fix loop from the Render & Validate section. This is where you'll catch visual issues that aren't obvious from JSON — overlaps, clipping, imbalanced composition.

Section Boundaries

Plan your sections around natural visual groupings from the diagram plan. A typical large diagram might split into:

• Section 1: Entry point / trigger
• Section 2: First decision or routing
• Section 3: Main content (hero section — may be the largest single section)
• Section 4-N: Remaining phases, outputs, etc.

Each section should be independently understandable: its elements, internal arrows, and any cross-references to adjacent sections.

What NOT to Do

• Don't generate the entire diagram in one response. You will hit the output token limit and produce truncated, broken JSON. Even if the diagram is small enough to fit, splitting into sections produces better results.
• Don't use a coding agent to generate the JSON. The agent won't have sufficient context about the skill's rules, and the coordination overhead negates any benefit.
• Don't write a Python generator script. The templating and coordinate math seem helpful but introduce a layer of indirection that makes debugging harder. Hand-crafted JSON with descriptive IDs is more maintainable.

Visual Pattern Library

Fan-Out (One-to-Many)

Central element with arrows radiating to multiple targets. Use for: sources, PRDs, root causes, central hubs.

        ○
       ↗
  □ → ○
       ↘
        ○

Convergence (Many-to-One)

Multiple inputs merging through arrows to single output. Use for: aggregation, funnels, synthesis.

  ○ ↘
  ○ → □
  ○ ↗

Tree (Hierarchy)

Parent-child branching with connecting lines and free-floating text (no boxes needed). Use for: file systems, org charts, taxonomies.

  label
  ├── label
  │   ├── label
  │   └── label
  └── label

Use line elements for the trunk and branches, free-floating text for labels.

Spiral/Cycle (Continuous Loop)

Elements in sequence with arrow returning to start. Use for: feedback loops, iterative processes, evolution.

  □ → □
  ↑     ↓
  □ ← □

Cloud (Abstract State)

Overlapping ellipses with varied sizes. Use for: context, memory, conversations, mental states.

Assembly Line (Transformation)

Input → Process Box → Output with clear before/after. Use for: transformations, processing, conversion.

  ○○○ → [PROCESS] → □□□
  chaos              order

Side-by-Side (Comparison)

Two parallel structures with visual contrast. Use for: before/after, options, trade-offs.

Gap/Break (Separation)

Visual whitespace or barrier between sections. Use for: phase changes, context resets, boundaries.

Lines as Structure

Use lines (type: line, not arrows) as primary structural elements instead of boxes:

• Timelines: Vertical or horizontal line with small dots (10-20px ellipses) at intervals, free-floating labels beside each dot
• Tree structures: Vertical trunk line + horizontal branch lines, with free-floating text labels (no boxes needed)
• Dividers: Thin dashed lines to separate sections
• Flow spines: A central line that elements relate to, rather than connecting boxes

Timeline:           Tree:
  ●─── Label 1        │
  │                   ├── item
  ●─── Label 2        │   ├── sub
  │                   │   └── sub
  ●─── Label 3        └── item

Lines + free-floating text often creates a cleaner result than boxes + contained text.

Shape Meaning

Choose shape based on what it represents—or use no shape at all:

Rule: Default to no container. Add shapes only when they carry meaning. Aim for <30% of text elements to be inside containers.

Color as Meaning

Colors encode information, not decoration. Every color choice should come from references/color-palette.md — the semantic shape colors, text hierarchy colors, and evidence artifact colors are all defined there.

Key principles:

• Each semantic purpose (start, end, decision, AI, error, etc.) has a specific fill/stroke pair
• Free-floating text uses color for hierarchy (titles, subtitles, details — each at a different level)
• Evidence artifacts (code snippets, JSON examples) use their own dark background + colored text scheme
• Always pair a darker stroke with a lighter fill for contrast

Do not invent new colors. If a concept doesn't fit an existing semantic category, use Primary/Neutral or Secondary.

Modern Aesthetics

For clean, professional diagrams:

Roughness

• roughness: 0 — Clean, crisp edges. Use for modern/technical diagrams.
• roughness: 1 — Hand-drawn, organic feel. Use for brainstorming/informal diagrams.

Default to 0 for most professional use cases.

Stroke Width

• strokeWidth: 1 — Thin, elegant. Good for lines, dividers, subtle connections.
• strokeWidth: 2 — Standard. Good for shapes and primary arrows.
• strokeWidth: 3 — Bold. Use sparingly for emphasis (main flow line, key connections).

Opacity

Always use opacity: 100 for all elements. Use color, size, and stroke width to create hierarchy instead of transparency.

Small Markers Instead of Shapes

Instead of full shapes, use small dots (10-20px ellipses) as:

• Timeline markers
• Bullet points
• Connection nodes
• Visual anchors for free-floating text

Layout Principles

Hierarchy Through Scale

• Hero: 300×150 - visual anchor, most important
• Primary: 180×90
• Secondary: 120×60
• Small: 60×40

Whitespace = Importance

The most important element has the most empty space around it (200px+).

Flow Direction

Guide the eye: typically left→right or top→bottom for sequences, radial for hub-and-spoke.

Connections Required

Position alone doesn't show relationships. If A relates to B, there must be an arrow.

Text Rules

CRITICAL: The JSON text property contains ONLY readable words.

{
  "id": "myElement1",
  "text": "Start",
  "originalText": "Start"
}

Settings: fontSize: 16, fontFamily: 3, textAlign: "center", verticalAlign: "middle"

JSON Structure

{
  "type": "excalidraw",
  "version": 2,
  "source": "https://excalidraw.com",
  "elements": [...],
  "appState": {
    "viewBackgroundColor": "#ffffff",
    "gridSize": 20
  },
  "files": {}
}

Element Templates

See references/element-templates.md for copy-paste JSON templates for each element type (text, line, dot, rectangle, arrow). Pull colors from references/color-palette.md based on each element's semantic purpose.

Worked Examples

references/examples/ holds full diagrams that realize this methodology — each a real .excalidraw file paired with its rendered PNG, with references/examples/README.md explaining what each one demonstrates. These are exemplars, not fill-in templates: study the moves (shape-as-meaning, color-as-argument, evidence artifacts, multi-zoom), then design your own.

• cicd-pipeline — simple/moderate: assembly-line flow, a decision diamond that branches pass/fail by color, evidence chips with real commands.
• oauth-authcode-flow — comprehensive/technical: a sequence diagram whose front-/back-channel coloring carries the security argument, plus dark evidence panels showing the actual RFC 6749 token exchange.

Using icons in architecture diagrams

For technical cloud/infra architecture diagrams, you can place real service icons (AWS, Azure, GCP, K8s) instead of generic rectangles. Icons are the concrete detail layer — the structure, flow, and visual argument are still yours to author (this is not license to drop icons in a uniform grid; that's "display", not "argue").

Only when a library is installed. Check references/libraries/ for a <set>/reference.md. If none exists, tell the user how to add one (see references/libraries/README.md) — don't invent icons.

Workflow:

1. Read references/libraries/<set>/reference.md to pick icons by name. It lists each icon's size so you can plan spacing — never open the icon JSON files, that's what the placement script is for.
2. Place each icon deterministically (icon JSON never enters your context):

   cd references
   uv run python scripts/place_icon.py --diagram <file.excalidraw> \
       --icon "Lambda" --library libraries/aws --x 400 --y 240 [--label "Auth"]
   

   It offsets the icon to (x, y), regenerates all ids/groups so repeated placements never collide, merges image data for raster icons, and appends to the diagram. Flags: --anchor center, --scale <f> (best-effort), --label (see below).
3. Hand-author the connectors, labels, and evidence artifacts yourself, per the methodology — icons don't make the argument, your layout does.
4. Run the normal render → view → fix loop. Icon spacing/overlap is caught there.

Gotchas:

• Many cloud icons embed their own name text — for those, omit --label or you'll double the caption. Render once to check.
• Fidelity: community icons are recognizable and correctly colored but hand-drawn style, not official-flat vendor icons. Set expectations accordingly.
• Sizes vary (~60–170px); read the size column and space accordingly.

Render & Validate (MANDATORY)

You cannot judge a diagram from JSON alone. After generating or editing the Excalidraw JSON, you MUST render it to PNG, view the image, and fix what you see — in a loop until it's right. This is a core part of the workflow, not a final check.

How to Render

cd .claude/skills/excalidraw-diagram/references && uv run python render_excalidraw.py <path-to-file.excalidraw>

This outputs a PNG next to the .excalidraw file. Then use the Read tool on the PNG to actually view it.

Rendering is offline after a one-time engine download. The fonts are vendored under references/vendor/; the Excalidraw engine (vendor/excalidraw.mjs) is fetched once on first render from a pinned, sha256-verified GitHub Release (see vendor/bundle.lock.json) — exactly like playwright install chromium — then served locally. So a failed first fetch is a network problem; a render that fails after the engine is present is not — the renderer prints the real cause and exits non-zero within a few seconds. If the download fails, build the engine locally with references/scripts/vendor.sh.

The Loop

After generating the initial JSON, run this cycle:

1. Render & View — Run the render script, then Read the PNG.

2. Audit against your original vision — Before looking for bugs, compare the rendered result to what you designed in Steps 1-4. Ask:

• Does the visual structure match the conceptual structure you planned?
• Does each section use the pattern you intended (fan-out, convergence, timeline, etc.)?
• Does the eye flow through the diagram in the order you designed?
• Is the visual hierarchy correct — hero elements dominant, supporting elements smaller?
• For technical diagrams: are the evidence artifacts (code snippets, data examples) readable and properly placed?

3. Check for visual defects:

• Text clipped by or overflowing its container
• Text or shapes overlapping other elements
• Arrows crossing through elements instead of routing around them
• Arrows landing on the wrong element or pointing into empty space
• Labels floating ambiguously (not clearly anchored to what they describe)
• Uneven spacing between elements that should be evenly spaced
• Sections with too much whitespace next to sections that are too cramped
• Text too small to read at the rendered size
• Overall composition feels lopsided or unbalanced

4. Fix — Edit the JSON to address everything you found. Common fixes:

• Widen containers when text is clipped
• Adjust x/y coordinates to fix spacing and alignment
• Add intermediate waypoints to arrow points arrays to route around elements
• Reposition labels closer to the element they describe
• Resize elements to rebalance visual weight across sections

5. Re-render & re-view — Run the render script again and Read the new PNG.

6. Repeat — Keep cycling until the diagram passes both the vision check (Step 2) and the defect check (Step 3). Typically takes 2-4 iterations. Don't stop after one pass just because there are no critical bugs — if the composition could be better, improve it.

When to Stop

The loop is done when:

• The rendered diagram matches the conceptual design from your planning steps
• No text is clipped, overlapping, or unreadable
• Arrows route cleanly and connect to the right elements
• Spacing is consistent and the composition is balanced
• You'd be comfortable showing it to someone without caveats

First-Time Setup

If the render script hasn't been set up yet:

cd .claude/skills/excalidraw-diagram/references
uv sync
uv run playwright install chromium

Quality Checklist

Depth & Evidence (Check First for Technical Diagrams)

1. Research done: Did you look up actual specs, formats, event names?
2. Evidence artifacts: Are there code snippets, JSON examples, or real data?
3. Multi-zoom: Does it have summary flow + section boundaries + detail?
4. Concrete over abstract: Real content shown, not just labeled boxes?
5. Educational value: Could someone learn something concrete from this?

Conceptual

6. Isomorphism: Does each visual structure mirror its concept's behavior?
7. Argument: Does the diagram SHOW something text alone couldn't?
8. Variety: Does each major concept use a different visual pattern?
9. No uniform containers: Avoided card grids and equal boxes?

Container Discipline

10. Minimal containers: Could any boxed element work as free-floating text instead?
11. Lines as structure: Are tree/timeline patterns using lines + text rather than boxes?
12. Typography hierarchy: Are font size and color creating visual hierarchy (reducing need for boxes)?

Structural

13. Connections: Every relationship has an arrow or line
14. Flow: Clear visual path for the eye to follow
15. Hierarchy: Important elements are larger/more isolated

Technical

16. Text clean: text contains only readable words
17. Font: fontFamily: 3
18. Roughness: roughness: 0 for clean/modern (unless hand-drawn style requested)
19. Opacity: opacity: 100 for all elements (no transparency)
20. Container ratio: <30% of text elements should be inside containers

Visual Validation (Render Required)

21. Rendered to PNG: Diagram has been rendered and visually inspected
22. No text overflow: All text fits within its container
23. No overlapping elements: Shapes and text don't overlap unintentionally
24. Even spacing: Similar elements have consistent spacing
25. Arrows land correctly: Arrows connect to intended elements without crossing others
26. Readable at export size: Text is legible in the rendered PNG
27. Balanced composition: No large empty voids or overcrowded regions