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.
git clone --depth 1 https://github.com/curiositech/some_claude_skillsWrote 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/plugins/curiositech/some_claude_skills/clip-aware-embeddings)<a href="https://agentmods.dev/plugins/curiositech/some_claude_skills/clip-aware-embeddings"><img src="https://agentmods.dev/badge/plugins/curiositech/some_claude_skills/clip-aware-embeddings.svg" alt="Measured on agentmods" height="20"></a>Grade A, and why
clip-aware-embeddings 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 today.
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.
What it actually says
{
"name": "clip-aware-embeddings",
"description": "Semantic image-text matching with CLIP and alternatives. Use for image search, zero-shot classification, similarity matching. NOT for counting objects, fine-grained classification (celebrities, car models), spatial reasoning, or compositional queries. Activate on \"CLIP\", \"embeddings\", \"image similarity\", \"semantic search\", \"zero-shot classification\", \"image-text matching\"."
}
What it installs
The manifest is a name and a version. 1 skill travel with it, and installing the plugin installs all of them — 82 tokens a session between them. Each is measured on its own page, and each can be installed alone.
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.
- today First seen · 5 lines scan A 6f3c3e510c3e
clip-aware-embeddings is a plugin published in the GitHub repository curiositech/some_claude_skills (211 stars, last pushed today), licensed MIT. Its token cost is not measured: this kind of file is read by the harness, not the model. 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 2026-09-06.
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