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.

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.

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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 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.

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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).

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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 (RUNSTARTED, STATEDELTA, A2UI_UPDATE)" → "CopilotKit renders via createA2UIMessageRenderer()"

Research makes diagrams accurate AND educational.

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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):

| Artifact Type | When to Use | How to Render | |---------------|-------------|---------------| | Code snippets | APIs, integrations, implementation details | Dark rectangle + syntax-colored text (see color palette for evidence artifact colors) | | Data/JSON examples | Data formats, schemas, payloads | Dark rectangle + colored text (see color palette) | | Event/step sequences | Protocols, workflows, lifecycles | Timeline pattern (line + dots + labels) | | UI mockups | Showing actual output/results | Nested rectangles mimicking real UI | | Real input content | Showing what goes IN to a system | Rectangle with sample content visible | | API/method names | Real function calls, endpoints | Use actual names from docs, not placeholders |

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.

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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

| Bad (Displaying) | Good (Arguing) | |------------------|----------------| | 5 equal boxes with labels | Each concept has a shape that mirrors its behavior | | Card grid layout | Visual structure matches conceptual structure | | Icons decorating text | Shapes that ARE the meaning | | Same container for everything | Distinct visual vocabulary per concept | | Everything in a box | Free-floating text with selective containers |

Simple vs Comprehensive (Know Which You Need)

| Simple Diagram | Comprehensive Diagram | |----------------|----------------------| | Generic labels: "Input" → "Process" → "Output" | Specific: shows what the input/output actually looks like | | Named boxes: "API", "Database", "Client" | Named boxes + examples of actual requests/responses | | "Events" or "Messages" label | Timeline with real event/message names from the spec | | "UI" or "Dashboard" rectangle | Mockup showing actual UI elements and content | | ~30 seconds to explain | ~2-3 minutes of teaching content | | Viewer learns the structure | Viewer learns the structure AND the details |

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.

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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.

| Use a Container When... | Use Free-Floating Text When... | |------------------------|-------------------------------| | It's the focal point of a section | It's a label or description | | It needs visual grouping with other elements | It's supporting detail or metadata | | Arrows need to connect to it | It describes something nearby | | The shape itself carries meaning (decision diamond, etc.) | Typography alone creates sufficient hierarchy | | It represents a distinct "thing" in the system | It's a section title, subtitle, or annotation |

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.

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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:

| If the concept... | Use this pattern | |-------------------|------------------| | Spawns multiple outputs | Fan-out (radial arrows from center) | | Combines inputs into one | Convergence (funnel, arrows merging) | | Has hierarchy/nesting | Tree (lines + free-floating text) | | Is a sequence of steps | Timeline (line + dots + free-floating labels) | | Loops or improves continuously | Spiral/Cycle (arrow returning to start) | | Is an abstract state or context | Cloud (overlapping ellipses) | | Transforms input to output | Assembly line (before → process → after) | | Compares two things | Side-by-side (parallel with contrast) | | Separates into phases | Gap/Break (visual separation between sections) |

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.

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.

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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.

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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.

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Shape Meaning

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

| Concept Type | Shape | Why | |--------------|-------|-----| | Labels, descriptions, details | none (free-floating text) | Typography creates hierarchy | | Section titles, annotations | none (free-floating text) | Font size/weight is enough | | Markers on a timeline | small ellipse (10-20px) | Visual anchor, not container | | Start, trigger, input | ellipse | Soft, origin-like | | End, output, result | ellipse | Completion, destination | | Decision, condition | diamond | Classic decision symbol | | Process, action, step | rectangle | Contained action | | Abstract state, context | overlapping ellipse | Fuzzy, cloud-like | | Hierarchy node | lines + text (no boxes) | Structure through lines |

Rule: Default to no container. Add shapes only when they carry meaning. Aim for

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## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [ccomkhj](https://github.com/ccomkhj)
- **Source:** [ccomkhj/skills](https://github.com/ccomkhj/skills)
- **License:** MIT

Install and usage instructions live in the source repository linked above.