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 skills add metaspartan/cybara --skill huggingface-gradiogit clone --depth 1 https://github.com/metaspartan/cybaraWrote 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/metaspartan/cybara/huggingface-gradio)<a href="https://agentmods.dev/skills/metaspartan/cybara/huggingface-gradio"><img src="https://agentmods.dev/badge/skills/metaspartan/cybara/huggingface-gradio/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/metaspartan/cybara/huggingface-gradio"><img src="https://agentmods.dev/badge/skills/metaspartan/cybara/huggingface-gradio.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00027 | $0.00232 |
| Opus 5 | $0.00014 | $0.00116 |
| Sonnet 5 | $0.00005 | $0.00046 |
| Haiku 4.5 | $0.00003 | $0.00023 |
Grade A, and why
huggingface-gradio 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 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.
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
Hugging Face Gradio
Use Gradio for focused model demos, dataset tools, and internal evaluation interfaces.
Workflow
- Define the smallest input and output schema that demonstrates the workflow.
- Put model loading outside the request handler and bound concurrency, queue size, timeouts, and upload sizes.
- Validate file types and user input before inference.
- Build the app in a UV-managed environment and run it locally first.
- Exercise keyboard navigation, labels, loading, empty, error, cancellation, and mobile-width states.
- Measure cold start and warmed request latency.
- Add authentication before exposing private models, datasets, or outputs.
Do not enable a public share link or deploy a Space unless the user explicitly requests that external action. Before deployment, review secrets, repository visibility, hardware, sleep behavior, and expected cost.
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 · 22 lines · 27 tokens per session scan A 1a3a522247cd
huggingface-gradio is a skill published in the GitHub repository metaspartan/cybara (28 stars, last pushed yesterday), licensed MIT. It adds 27 tokens to every session and 232 once invoked, about $0.0001 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 2026-08-30.
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