Borrowing it
Nothing to install: this file belongs to nvdigitalsolutions/mcp-ai-wpoos. 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/nvdigitalsolutions/mcp-ai-wpoos/main/.agents/skills/design-image-optimization/SKILL.mdgit clone --depth 1 https://github.com/nvdigitalsolutions/mcp-ai-wpoosWrote 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/nvdigitalsolutions/mcp-ai-wpoos/design-image-optimization)<a href="https://agentmods.dev/skills/nvdigitalsolutions/mcp-ai-wpoos/design-image-optimization"><img src="https://agentmods.dev/badge/skills/nvdigitalsolutions/mcp-ai-wpoos/design-image-optimization/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/nvdigitalsolutions/mcp-ai-wpoos/design-image-optimization"><img src="https://agentmods.dev/badge/skills/nvdigitalsolutions/mcp-ai-wpoos/design-image-optimization.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 | $0.00104 | $0.02701 |
| Opus 5 | $0.00052 | $0.01350 |
| Sonnet 5 | $0.00021 | $0.00540 |
| Haiku 4.5 | $0.00010 | $0.00270 |
Grade B, and why
design-image-optimization 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 10d 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
const response = await fetch('http://localhost:3100/api/image/optimize', { method: 'POST', The source is not reproduced here
A licence we could not identify
The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.
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.
- 10d ago First seen · 264 lines · 104 tokens per session scan B 8cece85ced68
design-image-optimization is a skill published in the GitHub repository nvdigitalsolutions/mcp-ai-wpoos (5 stars, last pushed today), with no licence file. It adds 104 tokens to every session and 2,701 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it B with 1 finding (sends data to an external url). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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