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/olivomarco/github-copilot-token-optimization/excalidraw-diagramnpx skills add olivomarco/github-copilot-token-optimization --skill excalidraw-diagramgit clone --depth 1 https://github.com/olivomarco/github-copilot-token-optimizationWrote 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/olivomarco/github-copilot-token-optimization/excalidraw-diagram)<a href="https://agentmods.dev/skills/olivomarco/github-copilot-token-optimization/excalidraw-diagram"><img src="https://agentmods.dev/badge/skills/olivomarco/github-copilot-token-optimization/excalidraw-diagram.svg" alt="Measured on agentmods" 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 | $0.00034 | $0.05469 |
| Opus 5 | $0.00017 | $0.02735 |
| Sonnet 5 | $0.00007 | $0.01094 |
| Haiku 4.5 | $0.00003 | $0.00547 |
Grade B, and why
excalidraw-diagram scanned grade B with 1 finding 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 5d 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.
Subtle steeringmediumPrompt injection
Instructions that bias recommendations or shape behaviour without the user noticing.
- **Don't write a Python generator script.** The templating and coordinate math seem helpful but introduce a layer of indirection that makes debugging harder. Hand-crafted JSON with descriptive IDs is more maintainable. The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 5d ago First seen · 553 lines · 34 tokens per session scan B f737a9720455
excalidraw-diagram is a skill published in the GitHub repository olivomarco/github-copilot-token-optimization (152 stars, last pushed 1mo ago), with no licence file. It adds 34 tokens to every session and 5,469 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (subtle steering). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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