Borrowing it
Nothing to install: this file belongs to abuango/pos-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/abuango/pos-ai/main/.claude/skills/excalidraw/SKILL.mdgit clone --depth 1 https://github.com/abuango/pos-aiWrote 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.
[](https://agentmods.dev/skills/abuango/pos-ai/excalidraw)<a href="https://agentmods.dev/skills/abuango/pos-ai/excalidraw"><img src="https://agentmods.dev/badge/skills/abuango/pos-ai/excalidraw/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.
<a href="https://agentmods.dev/skills/abuango/pos-ai/excalidraw"><img src="https://agentmods.dev/badge/skills/abuango/pos-ai/excalidraw.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00058 | $0.01135 |
| Opus 5.5 | $0.00023 | $0.00454 |
| Sonnet 5.5 | $0.00012 | $0.00227 |
| Haiku 4.5 | $0.00006 | $0.00113 |
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 2mo 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Excalidraw Diagram Generator
Setup
Before starting: check .handoff/sessions/ for active sessions, read context status.yaml, run git status. Follow .rules/universal.md (Plan -> Approve -> Execute).
You generate production-quality Excalidraw diagrams from natural language descriptions or codebase analysis. Diagrams should argue, not just display — visual structure maps to conceptual structure.
Process
Step 1: Understand What to Diagram
- From description — Parse the user's natural language description
- From codebase — Analyze source code to extract component relationships
- Determine diagram type:
- System architecture (components + connections)
- Data flow (how data moves through the system)
- Sequence diagram (request lifecycle)
- Deployment topology (infrastructure layout)
- Entity relationship (data model)
Step 2: Map Concepts to Visual Structure
Apply these design principles:
- Fan-out structures for one-to-many relationships
- Timeline/sequence layouts for sequential flows
- Convergence shapes for aggregation points
- Grouping boxes for bounded contexts or services
- Color coding for different concerns (data stores = blue, services = green, external = orange, clients = purple)
- Never use uniform card grids — structure must reflect the actual relationships
Step 3: Generate Excalidraw JSON
Generate a valid Excalidraw JSON file with:
- Properly positioned elements (no overlaps)
- Arrow connections between related components
- Consistent font sizes (title: 28, component: 20, label: 16, annotation: 14)
- Adequate spacing (minimum 40px between elements)
- Grouped related elements
Step 4: Self-Validate
Before delivering, check:
- No overlapping text or elements
- All arrows connect to the correct source/target
- Layout is balanced (not lopsided)
- Labels are readable (not truncated)
- Color usage is consistent and meaningful
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.
- 2mo ago First seen · 127 lines · 58 tokens per session scan A 2b03ebd911b3
excalidraw is a skill published in the GitHub repository abuango/pos-ai (2 stars, last pushed 7mo ago), licensed MIT. It adds 58 tokens to every session and 1,135 once invoked, about $0.0002 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 2026-08-31.
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