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-papersgit 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-papers)<a href="https://agentmods.dev/skills/metaspartan/cybara/huggingface-papers"><img src="https://agentmods.dev/badge/skills/metaspartan/cybara/huggingface-papers/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-papers"><img src="https://agentmods.dev/badge/skills/metaspartan/cybara/huggingface-papers.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 | $0.00030 | $0.00240 |
| Opus 5 | $0.00015 | $0.00120 |
| Sonnet 5 | $0.00006 | $0.00048 |
| Haiku 4.5 | $0.00003 | $0.00024 |
Grade A, and why
huggingface-papers 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 9d 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 Papers
Use hf papers list --format json or the Hub papers pages for discovery, then inspect the original paper before relying on a claim.
Workflow
- Capture the title, authors, publication date, paper URL, and stable identifier.
- Read the abstract, method, training data, evaluation setup, ablations, limitations, and license.
- Follow linked model, dataset, code, and demo repositories only when they are relevant.
- Distinguish author claims from reproduced or independently verified results.
- Compare metrics only when tasks, splits, prompts, baselines, and compute settings are compatible.
- Cite the original paper and primary artifacts near each technical claim.
Do not infer implementation details that are absent from the paper or its linked source. State when evidence is missing, unpublished, or not reproducible from available artifacts.
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.
- 9d ago First seen · 21 lines · 30 tokens per session scan A 00695333e811
huggingface-papers is a skill published in the GitHub repository metaspartan/cybara (28 stars, last pushed yesterday), licensed MIT. It adds 30 tokens to every session and 240 once invoked, about $0.0002 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.
Other skills, from other repositories
academic-paper-review
Use this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation.…
papyrus-writing
LaTeX paper writing and editing. Load when working on a .tex document — writing or revising sections, fixing compilation errors, adding figures/tables/equations, or managing a bibliography. Also the co-author skill for the Papyrus app.
personal-genomics
Analyse personal DNA / genome files for pharmacogenomics, disease risk, carrier status, ancestry and traits. Use whenever the user mentions DNA or genome analysis, a raw genome file, gene names, drug-gene interactions, or wants to combine multiple DNA sources.
Jupyter Live Kernel
Guides notebook-first analysis with reproducible kernels, inspectable data loading, and explicit promotion paths back into durable code.
kodama-verification
Define measurable success criteria and collect targeted test, build, lint, type-check, or smoke-test evidence before claiming work is complete.
arXiv
Search, filter, and summarize arXiv papers with explicit titles, authors, dates, and paper links before drawing conclusions.