excalidraw-it

excalidraw-it is a skill for Claude Code from alberduris/skills. It costs 88 tokens per session (1,238 once invoked), scanned A, original, MIT.

A diagram-drawing workflow that uses the Excalidraw+ MCP to write diagrams into a live workspace. MCP is a connection that lets an agent use an external tool, while the operator can view and correct the scene in a browser.

In plain words
What is it for?
It is for creating supported diagrams from structured input, updating a shared scene, and applying lint checks to the result.
Why use it?
It gives diagram generation a defined process, including format guidance and checks for known canvas mistakes.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Part of the excalidraw-it plugin — 1 skill shipped together

Good fit It is for creating supported diagrams from structured input, updating a shared scene, and applying lint checks to the result.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/alberduris/skills/excalidraw-it
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add alberduris/skills --skill excalidraw-it
Clone the repo
git clone --depth 1 https://github.com/alberduris/skills

Made for: Claude Code.

Or install excalidraw-it, the plugin that ships this one along with the rest of its 1 skill.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for excalidraw-it

README.md
[![agentmods](https://agentmods.dev/badge/skills/alberduris/skills/excalidraw-it/github.svg)](https://agentmods.dev/skills/alberduris/skills/excalidraw-it)
Your own site
<a href="https://agentmods.dev/skills/alberduris/skills/excalidraw-it"><img src="https://agentmods.dev/badge/skills/alberduris/skills/excalidraw-it/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for excalidraw-it

Your own site · 80×15
<a href="https://agentmods.dev/skills/alberduris/skills/excalidraw-it"><img src="https://agentmods.dev/badge/skills/alberduris/skills/excalidraw-it.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 88 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,238 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00088 $0.01238
Opus 5.5 $0.00035 $0.00495
Sonnet 5.5 $0.00018 $0.00248
Haiku 4.5 $0.00009 $0.00124

Measured 18d ago against content hash 3d07860c099b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

excalidraw-it scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 18d ago.

The scan reads SKILL.md. This mod also ships 16 executable files (checks/broken_word.py, checks/clipped_text_end.py, checks/fallback_glyph.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/excalidraw-it/skills/excalidraw-it/SKILL.md · 46 lines

How it starts

The opening of the file, as written. The whole thing — 46 lines — stays where its author put it; the contents beside it link to each section on GitHub.

A diagram here is a scene in the operator's Excalidraw+ workspace. You write it through the MCP, and the operator's browser shows each write as soon as the server saves it. The operator edits the scene by hand only to correct something, and tells you when they do: read back only the elements they name, never the whole scene.

[!SETUP]:

  1. Before the first JSON you write by hand, or the first create_diagram, call the format guide that matches the task, once per session: read_diagram_format, read_freeform_format or read_presentation_format. It costs about 10k tokens. Skip it while draw.py, pieces.py or mermaid.py write every element: their payloads already follow the format.
  2. Use an existing scene id, or create_scene in the collection the operator names; with none named, in the one list_collections marks isDefault: true (private works only with a personal API key). Give the operator the link https://app.excalidraw.com/s/<workspace>/<sceneId>, with metadata.workspace and metadata.id of the create_scene response.

[!TYPES]:

python3 <base_directory>/scripts/draw.py --help lists the diagram types that have a generator: a script that draws the whole diagram, title and note included, from its data in YAML. For one of them, draw.py <type> --help shows the YAML it takes, and it is all you need to read: write the data and run python3 <base_directory>/scripts/draw.py <type> data.yaml | python3 <base_directory>/scripts/write.py <sceneId>. To change a generated diagram, change its data and draw it again: first send {"delete": [...]} with the addedElementIds of its write answer, and their labels go with them. Edit elements by hand only for what the data cannot say. For a type with no generator, read its entry in ledger/types.yaml: which route draws it (create_diagram, Mermaid through mermaid-to-excalidraw, or by hand with edit_scene_content) and why the others are vetoed. A type with no entry: draw it by hand from the entry of the closest type, and propose an entry for it to the operator.

[!EVERY-WRITE]:

  1. Before you write JSON by hand, check the plan against the sins and use every piece from the ledger that fits; a generator already does both.
  2. Write through python3 <base_directory>/scripts/write.py <sceneId>, with the payload on stdin: an add array, or an object with delete, update and add. It calls edit_scene_content over HTTP and prints one line; the full answer goes to $TMPDIR/excalidraw-it/.
  3. After the write, run python3 <base_directory>/scripts/lint.py <sceneId> --fix. It applies the fix of every finding and lints the scene again.
  4. Once the lint is clean, call take_screenshot before you show the result. Render per frame when the scene is larger than one screen, because a full-scene render is scaled down to 1920x1080 and small defects stop being visible.

[!READING]:

Each way of reading the scene costs a different amount of context. Measured on a scene of 107 elements:

  • search_scene_content with a query returns only the matching elements, about 200 tokens each. It matches shape labels and standalone text, and never returns the text of a label bound to a shape (containerId set), so it cannot tell you where a label sits.
  • get_scene_content returns every element: 73 KB, about 20k tokens. Never call it.
  • python3 <base_directory>/scripts/fetch.py <sceneId> downloads the same content through the REST API into a local file, with the key in EXCALIDRAW_API_KEY. Query that file with Python and print only the fields you need. Use it for every question about geometry: label padding, arrow endpoints, overlaps.
  • take_screenshot costs between a few hundred tokens and about 3k, depending on the render size. To check a layout, it is cheaper than reading the JSON.

edit_scene_content answers with the id and position of each element it added: about 4k tokens for 83 elements.

[!SINS]:

ledger/sins.yaml lists the mistakes agents make on the canvas again and again i.e., what happens, and the rule that prevents it. Read it before the first write by hand. Each sin has a lint check with the same id, except the ones marked lint: none.

Read the full file on GitHub · 46 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 18d ago First seen · 46 lines · 88 tokens per session scan A 3d07860c099b

Subscribe to this mod's changes

excalidraw-it is a skill published in the GitHub repository alberduris/skills (20 stars, last pushed 15d ago), licensed MIT. It adds 88 tokens to every session and 1,238 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-01.

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