# ExcaliDraw Skill Pack

> Use this tool when you need to create high-quality diagrams with AI agents, solving problems of visual representation and documentation. The ExcaliDraw Skill Pack accepts skeleton and Mermaid input and produces publishable output in 5 different themes, making it ideal for use cases requiring clear and concise visual communication. It is particularly useful in contexts where technical diagrams need to be generated and rendered efficiently, such as in documentation, education, or presentation materials.

Canonical page: https://skillsregistry.net/skills/isatimur-excalidraw-skill-pack  
JSON: https://api.skillsregistry.net/v1/skills/isatimur-excalidraw-skill-pack

## Description

The diagram-quality layer for AI agents — an opinionated Excalidraw methodology (isomorphism test, evidence artifacts, multi-zoom, container discipline) plus a render-view-fix loop. Accepts skeleton and Mermaid input, 5 publishable themes, dual Node/Python renderer.
Proven on a 77-diagram published book.

## Trust

- **Trust score (0–1):** 0.31
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/ajdm7f4xl3)
- **Repository:** <https://github.com/isatimur/excalidraw-skill-pack>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "isatimur-excalidraw-skill-pack"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/isatimur-excalidraw-skill-pack` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/isatimur-excalidraw-skill-pack/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt