excalidraw

A helper for working with Excalidraw files, which are editable drawings used for diagrams and flowcharts. It delegates diagram tasks so the agent does not have to process the files’ large amount of drawing metadata.

In plain words
What is it for?
Work with .excalidraw files, create or explain flowcharts, update diagrams, and visualize software architecture or other processes.
Why use it?
It avoids wasting context on visual formatting details that contain little useful information. This makes it practical to create, explain, or update diagrams and architecture drawings.

Skill for Claude CodeCodex

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.

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

Made for: Claude Code, Codex.

Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,895 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00069 $0.01895
Opus 5 $0.00034 $0.00948
Sonnet 5 $0.00014 $0.00379
Haiku 4.5 $0.00007 $0.00189

Measured 3d ago against content hash 561c01a2b0c7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

excalidraw 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 3d ago.

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.

skills/excalidraw/SKILL.md · 222 lines

How it starts

The opening of the file, as written. The whole thing — 222 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Excalidraw Subagent Delegation

Overview

Core principle: Main agents NEVER read Excalidraw files directly. Always delegate to subagents to isolate context consumption.

Excalidraw files are JSON with high token cost but low information density. Single files range from 4k-22k tokens (largest can exceed read tool limits). Reading multiple diagrams quickly exhausts context budget (7 files = 67k tokens = 33% of budget).

The Problem

Excalidraw JSON structure:

  • Each shape has 20+ properties (x, y, width, height, strokeColor, seed, version, etc.)
  • Most properties are visual metadata (positioning, styling, roughness)
  • Actual content: text labels and element relationships (<10% of file)
  • Signal-to-noise ratio is extremely low

Example: 14-element diagram = 596 lines, 16K, ~4k tokens. 79-element diagram = 2,916 lines, 88K, ~22k tokens (exceeds read limit).

When to Use

Trigger on ANY of these:

  • File path contains .excalidraw or .excalidraw.json
  • User requests: "explain/update/create diagram", "show architecture", "visualize flow"
  • User mentions: "flowchart", "architecture diagram", "Excalidraw file"
  • Architecture/design documentation tasks involving visual artifacts

Use delegation even for:

  • "Small" files (smallest is 4k tokens - still significant)
  • "Quick checks" (checking component names still loads full JSON)
  • Single file operations (isolation prevents context pollution)
  • Modifications (don't need full format understanding in main context)

Delegation Pattern

Main Agent Responsibilities

NEVER:

  • ❌ Use Read tool on *.excalidraw files
  • ❌ Parse Excalidraw JSON in main context
  • ❌ Load multiple diagrams for comparison
  • ❌ Inspect file to "understand the format"

ALWAYS:

  • ✅ Delegate ALL Excalidraw operations to subagents
  • ✅ Provide clear task description to subagent
  • ✅ Request text-only summaries (not raw JSON)
  • ✅ Keep diagram analysis isolated from main work

Subagent Task Templates

Read/Understand Operation
Task: Extract and explain the components in [file.excalidraw.json]

Approach:
1. Read the Excalidraw JSON
2. Extract only text elements (ignore positioning/styling)
3. Identify relationships between components
4. Summarize architecture/flow

Return:
- List of components/services with descriptions
- Connection/dependency relationships
- Key insights about the architecture
- DO NOT return raw JSON or verbose element details

Read the full file on GitHub · 222 lines

Files

What ships with it

1 file 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. 3d ago First seen · 222 lines · 69 tokens per session scan A 561c01a2b0c7

Subscribe to this mod's changes

excalidraw is a skill published in the GitHub repository softaworks/agent-toolkit (2,413 stars, last pushed 6mo ago), licensed MIT. It adds 69 tokens to every session and 1,895 once invoked, about $0.0003 per session on Opus 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 2026-08-30.