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hf-papers高频论文

Agent Skill

hf-papers 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

11,781

周安装

472

GitHub Stars

公开资料未说明

下载量

3,814
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:hf-papers(高频论文)
来源仓库:https://github.com/willamhou/hf-papers
安装命令:
openclaw skills install hf-papers
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install hf-papers

简介

浏览热门论文,按关键词搜索,并从 Hugging Face Papers 获取论文详细信息

SKILL.md

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]

hf-papers

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.

Description

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.

Usage Examples

  • "What are today's trending papers on Hugging Face?"
  • "Search Hugging Face Papers for diffusion models"
  • "Get details for paper 2401.12345 on HF"
  • "Show me comments on HF paper 2405.67890"

Process

  1. Discover — Use hf_daily_papers to see what's trending today
  2. Search — Use hf_search_papers to find papers on a topic
  3. Inspect — Use hf_paper_detail to get full metadata for a specific paper
  4. Discuss — Use hf_paper_comments to read community discussion
  5. Deep read — Use arxiv_fetch (from arxiv-reader) with the paper's arXiv ID for full text

Tools

hf_daily_papers

Get 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" }

hf_search_papers

Search Hugging Face Papers by keyword.

Parameters:

  • query (string, required): Search query

Returns: { papers: [{ id, title, summary, upvotes, authors, publishedAt, githubRepo?, projectPage?, ai_summary? }], query: string, count: number }

Example:

{ "query": "multimodal reasoning" }

hf_paper_detail

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" }

hf_paper_comments

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" }

Notes

  • All results are cached locally — repeat requests are instant (15-minute TTL for daily/search, 1-hour for details)
  • Paper IDs are arXiv IDs — use with arxiv-reader skill for full LaTeX text
  • No authentication required; uses HF public API
  • Daily papers update throughout the day as the community submits and upvotes

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

85.98%
按下载量换算3,279

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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