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HF Papers

作者 Will.hou · GitHub ↗ · v1.0.3 · MIT-0
cross-platform ✓ 安全检测通过
374
总下载
0
收藏
0
当前安装
4
版本数
在 OpenClaw 中安装
/install hf-papers
功能描述
Browse trending papers, search by keyword, and get paper details from Hugging Face Papers
使用说明 (SKILL.md)

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
安全使用建议
This skill appears coherent and low-risk: it queries the public Hugging Face Papers API and caches results under ~/.cache/hf-papers/ (15-minute/1-hour TTLs). There are no install steps, no downloads, and no credentials requested. If you are concerned about local data, you can remove that cache directory after use. Note that because this is an instruction-only skill (no code files), its runtime network behavior depends on the platform implementing the described tools — if you need stronger assurance, ask the maintainer or platform for details on the actual HTTP endpoints and caching implementation before installing.
功能分析
Type: OpenClaw Skill Name: hf-papers Version: 1.0.3 The skill bundle provides a standard interface for interacting with the Hugging Face Papers API to search and retrieve academic paper metadata. The tool definitions and instructions in SKILL.md are consistent with the stated purpose, and no indicators of data exfiltration, malicious execution, or prompt injection were found.
能力评估
Purpose & Capability
Name/description match the actions documented in SKILL.md (trending, search, details, comments). No unrelated credentials, binaries, or config paths are requested.
Instruction Scope
Instructions describe calling the Hugging Face Papers public API and optionally using an external arxiv-reader skill for full text. The only local I/O mentioned is caching under ~/.cache/hf-papers/ with specified TTLs; nothing instructs reading unrelated files or secrets.
Install Mechanism
No install spec or code files are present (instruction-only). This minimizes risk because nothing is downloaded or written by the skill itself during install.
Credentials
The skill requires no environment variables, credentials, or config paths. That is appropriate for a read-only public-API browsing/searching capability.
Persistence & Privilege
always is false and the skill does not request elevated or cross-skill configuration changes. Local caching is limited to a per-user cache directory (~/.cache/hf-papers/) and TTLs are defined.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install hf-papers
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /hf-papers 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.3
Remove executable code to resolve security flags
v1.0.2
- Initial skill release: browse, search, and get details for Hugging Face Papers. - Supports trending papers, keyword search, metadata lookup, and community comments. - No authentication required; results cached locally for fast repeat access. - Uses public Hugging Face Papers API; integrates with arxiv-reader for full paper text.
v1.0.1
- Removed core implementation and manifest files (`index.ts`, `manifest.json`). - The skill package now contains only documentation; no functionality is present in this version.
v1.0.0
Initial release of the hf-papers skill. - Browse trending papers, search by keyword, and get paper details from Hugging Face Papers. - Fetch metadata, upvote counts, author info, project/GitHub links, and community comments. - Results are cached locally for fast repeated access. - No authentication required; uses the public Hugging Face Papers API. - Integrates with arxiv-reader for full paper text using arXiv IDs.
元数据
Slug hf-papers
版本 1.0.3
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 4
常见问题

HF Papers 是什么?

Browse trending papers, search by keyword, and get paper details from Hugging Face Papers. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 374 次。

如何安装 HF Papers?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install hf-papers」即可一键安装,无需额外配置。

HF Papers 是免费的吗?

是的,HF Papers 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

HF Papers 支持哪些平台?

HF Papers 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 HF Papers?

由 Will.hou(@willamhou)开发并维护,当前版本 v1.0.3。

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