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Browse trending papers, search by keyword, and get paper details from Hugging Face Papers
Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.
Baseado na classificação ocupacional SOC
Fast headless browser automation for AI agents (Rust-based with Node.js fallback). Navigate, click, type, and snapshot pages via structured commands. Triggers on browser automation, headless browsing, page snapshot. NOT for: websites needing login/cookies (use bb-browser or browser profile), or simple URL content extraction (use web_fetch/firecrawl).
Search, download, and summarize academic papers from arXiv. Built for AI/ML researchers.
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自动化浏览器交互：网页测试、表单填写、截图、数据提取。触发：需要导航网站、与网页交互、填写表单、截图、提取信息。需要浏览器工具可用。不适用于简单 URL 抓取（用 web_fetch）、需要完整渲染的 JS 重度站点（用 firecrawl）、批量无头自动化（用 agent-browser）。
"通过 HTTP API 控制浏览器自动化：页面导航、元素交互（点击/输入/选择）、数据提取、无障碍快照、截图、JS 执行、批量操作。触发：需要通过 API 程序化控制浏览器。不适用于：一次性简单浏览器任务（用 agent-browser）、平台特定交互（用 bb-browser）。"
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| name | hf-papers |
| description | Browse trending papers, search by keyword, and get paper details from Hugging Face Papers |
| metadata | {"openclaw":{"emoji":"🤗","tags":["huggingface","research","academic","papers","trending"],"requires":{"bins":[],"os":["darwin","linux","win32"]}}} |
Browse, search, and analyze papers from the Hugging Face Papers platform. Get trending papers, search by topic, and retrieve detailed metadata including community engagement and linked resources.
This skill wraps the Hugging Face Papers public API. It provides access to daily trending papers, keyword search, paper details (abstract, authors, upvotes, GitHub repos, project pages), and discussion comments. No authentication required.
For full paper text, use the returned arXiv ID with the arxiv-reader skill.
Results are cached locally (~/.cache/hf-papers/) for fast repeat access.
hf_daily_papers to see what's trending todayhf_search_papers to find papers on a topichf_paper_detail to get full metadata for a specific paperhf_paper_comments to read community discussionarxiv_fetch (from arxiv-reader) with the paper's arXiv ID for full textGet today's trending papers from Hugging Face.
Parameters:
limit (number, optional): Max papers to return (default: 20, max: 100)sort (string, optional): Sort by upvotes or date (default: upvotes)Returns: { papers: [{ id, title, summary, upvotes, authors, publishedAt, githubRepo?, projectPage?, ai_summary?, ai_keywords? }], count: number }
Example:
{ "limit": 10, "sort": "upvotes" }
Search Hugging Face Papers by keyword.
Parameters:
query (string, required): Search queryReturns: { papers: [{ id, title, summary, upvotes, authors, publishedAt, githubRepo?, projectPage?, ai_summary? }], query: string, count: number }
Example:
{ "query": "multimodal reasoning" }
Get detailed metadata for a specific paper.
Parameters:
paper_id (string, required): Paper ID (arXiv ID, e.g. 2401.12345)Returns: { id, title, summary, authors, publishedAt, upvotes, numComments, githubRepo?, githubStars?, projectPage?, ai_summary?, ai_keywords?, organization? }
Example:
{ "paper_id": "2401.12345" }
Get discussion comments for a paper.
Parameters:
paper_id (string, required): Paper ID (arXiv ID)Returns: { paper_id, comments: [{ author, content, createdAt }], count: number }
Example:
{ "paper_id": "2401.12345" }
arxiv-reader skill for full LaTeX text