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.
npx agentmods add skills/zate/cc-plugins/excalidrawnpx skills add Zate/cc-plugins --skill excalidrawgit clone --depth 1 https://github.com/Zate/cc-pluginsWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00068 | $0.02487 |
| Opus 5 | $0.00034 | $0.01243 |
| Sonnet 5 | $0.00014 | $0.00497 |
| Haiku 4.5 | $0.00007 | $0.00249 |
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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Excalidraw Diagram Skill
Generate diagrams by writing .excalidraw files directly. The output is a JSON file in the Excalidraw format that can be opened in the Excalidraw desktop app, web app (excalidraw.com), VS Code extension, or Obsidian plugin.
IMPORTANT: Do NOT use the Excalidraw MCP tools (mcp__claude_ai_Excalidraw__*), even if they are available. We generate the file ourselves for full control over quality and layout. The MCP tools produce lower quality results and require uploading to excalidraw.com.
When to use Excalidraw:
- User explicitly asks for Excalidraw / whiteboard / sketch / hand-drawn style
- Diagrams for brainstorming, early design, or informal communication
- User wants an editable diagram file they can refine in Excalidraw
When another format is better:
- Formal documentation or whitepapers (SVG)
- Pixel-precise positioning (SVG)
- Inline in GitHub markdown (Mermaid)
Consult the design-system skill for color, composition, and quality rules.
Workflow
1. Plan the Layout
Before generating the file:
- Identify all elements (boxes, arrows, labels) and their relationships
- Plan the spatial layout on a grid (estimate x, y, width, height for each)
- Use generous spacing: 40-60px between peer elements, 20-30px padding inside groups
2. Build the Excalidraw JSON
An .excalidraw file is JSON with this top-level structure:
{
"type": "excalidraw",
"version": 2,
"source": "diagrams-plugin",
"elements": [ ... ],
"appState": {
"viewBackgroundColor": "#ffffff",
"gridSize": null
},
"files": {}
}
3. Write the File
Save with .excalidraw extension using the Write tool. The user handles viewing/rendering.
Element Format
Required Fields (all elements)
Every element needs: type, id (unique string), x, y, width, height, version, versionNonce, isDeleted, groupIds, boundElements, seed.
Use this template for default fields:
{
"version": 1,
"versionNonce": 1,
"isDeleted": false,
"fillStyle": "solid",
"strokeWidth": 2,
"strokeStyle": "solid",
"roughness": 1,
"opacity": 100,
"groupIds": [],
"frameId": null,
"roundness": null,
"seed": 1,
"updated": 1,
"locked": false,
"link": null
}
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.
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.
- 2d ago First seen · 290 lines · 68 tokens per session scan A ca646574e7ea
excalidraw is a skill published in the GitHub repository Zate/cc-plugins (10 stars, last pushed 1mo ago), licensed MIT. It adds 68 tokens to every session and 2,487 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…