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 BingHanOfUESTC/open_agent_team --skill huggingface-papersgit clone --depth 1 https://github.com/BingHanOfUESTC/open_agent_teamWrote 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/binghanofuestc/open_agent_team/huggingface-papers)<a href="https://agentmods.dev/skills/binghanofuestc/open_agent_team/huggingface-papers"><img src="https://agentmods.dev/badge/skills/binghanofuestc/open_agent_team/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/binghanofuestc/open_agent_team/huggingface-papers"><img src="https://agentmods.dev/badge/skills/binghanofuestc/open_agent_team/huggingface-papers.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 | $0.00078 | $0.02525 |
| Opus 5 | $0.00039 | $0.01262 |
| Sonnet 5 | $0.00016 | $0.00505 |
| Haiku 4.5 | $0.00008 | $0.00252 |
Grade A, and why
huggingface-papers scanned grade A 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 7d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s "https://huggingface.co/papers/{PAPER_ID}.md" This is a copy
100% identical to huggingface-papers — 476 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hugging Face Paper Pages
Hugging Face Paper pages (hf.co/papers) is a platform built on top of arXiv (arxiv.org), specifically for research papers in the field of artificial intelligence (AI) and computer science. Hugging Face users can submit their paper at hf.co/papers/submit, which features it on the Daily Papers feed (hf.co/papers). Each day, users can upvote papers and comment on papers. Each paper page allows authors to:
- claim their paper (by clicking their name on the
authorsfield). This makes the paper page appear on their Hugging Face profile. - link the associated model checkpoints, datasets and Spaces by including the HF paper or arXiv URL in the model card, dataset card or README of the Space
- link the Github repository and/or project page URLs
- link the HF organization. This also makes the paper page appear on the Hugging Face organization page.
Whenever someone mentions a HF paper or arXiv abstract/PDF URL in a model card, dataset card or README of a Space repository, the paper will be automatically indexed. Note that not all papers indexed on Hugging Face are also submitted to daily papers. The latter is more a manner of promoting a research paper. Papers can only be submitted to daily papers up until 14 days after their publication date on arXiv.
The Hugging Face team has built an easy-to-use API to interact with paper pages. Content of the papers can be fetched as markdown, or structured metadata can be returned such as author names, linked models/datasets/spaces, linked Github repo and project page.
When to Use
- User shares a Hugging Face paper page URL (e.g.
https://huggingface.co/papers/2602.08025) - User shares a Hugging Face markdown paper page URL (e.g.
https://huggingface.co/papers/2602.08025.md) - User shares an arXiv URL (e.g.
https://arxiv.org/abs/2602.08025orhttps://arxiv.org/pdf/2602.08025) - User mentions a arXiv ID (e.g.
2602.08025) - User asks you to summarize, explain, or analyze an AI research paper
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.
- 7d ago First seen · 239 lines · 78 tokens per session scan A 1cb8a2e3b8c8
huggingface-papers is a skill published in the GitHub repository BingHanOfUESTC/open_agent_team (106 stars, last pushed 2mo ago), licensed MIT. It adds 78 tokens to every session and 2,525 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 100% identical to huggingface-papers, differing in 476 lines, and is treated as a copy.
Other skills, from other repositories
company-product-context
Compiles comprehensive company product context from PDF documents, web research, and industry knowledge.
python-lib-analyzer
Analyze any Python library structure, explore modules, classes, and functions with signatures and documentation.
Ability Generator
This skill generates markdown skill templates to be later used.
nexus-configuration
A skill for reading, planning, approving, and checking configuration in Nexus, the current private conversation or room. It covers settings such as agents, rooms, providers, channels, connectors, skills, models, tools, and MCP connections.
agentica
How to answer questions about the agentica product you are running inside — CLI flags, config.yaml profiles, API keys, models, sessions, resume, workspace, AGENTS.md standing rules, skills, logs, upgrade, and selfmanage. Use when asked how agentica works, how to configure or upgrade it, where state lives on disk…
generate-ai-rules
Generate AI assistant configuration files for a repository — CLAUDE.md, AGENTS.md, and Cursor rules (.cursor/rules/.mdc) — from codebase analysis. Use whenever the user wants to create or update CLAUDE.md, AGENTS.md, agent rules, Cursor rules, AI coding assistant configuration, or "onboard AI tools" to a project, even…