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hugging-face-paper-pages拥抱面纸页

Agent Skill

hugging-face-paper-pages 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

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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

unknown

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:hugging-face-paper-pages(拥抱面纸页)
来源仓库:https://github.com/huggingface/skills
仓库路径:skills/hugging-face-paper-pages
安装命令:
npx skills add https://github.com/huggingface/skills --skill hugging-face-paper-pages
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/huggingface/skills --skill hugging-face-paper-pages

简介

用于查找、检索和筛选相关信息,支持基于关键词或任务场景定位内容。

  • 适用于学术研究、资料收集或技术调研等检索类任务。
  • 可通过 npx skills add 从 Hugging Face 官方仓库安装。
  • 注意检查技能是否具备联网能力及相关安全风险。
  • hugging-face-paper-pages 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

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 authors field). 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/2602.08025 or https://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

Parsing the paper ID

It's recommended to parse the paper ID (arXiv ID) from whatever the user provides:

InputPaper ID
https://huggingface.co/papers/2602.080252602.08025
https://huggingface.co/papers/2602.08025.md2602.08025
https://arxiv.org/abs/2602.080252602.08025
https://arxiv.org/pdf/2602.080252602.08025
2602.08025v12602.08025v1
2602.080252602.08025

This allows you to provide the paper ID into any of the hub API endpoints mentioned below.

Fetch the paper page as markdown

The content of a paper can be fetched as markdown like so:

curl -s "https://huggingface.co/papers/{PAPER_ID}.md"

This should return the Hugging Face paper page as markdown. This relies on the HTML version of the paper at https://arxiv.org/html/{PAPER_ID}.

There are 2 exceptions:

  • Not all arXiv papers have an HTML version. If the HTML version of the paper does not exist, then the content falls back to the HTML of the Hugging Face paper page.
  • If it results in a 404, it means the paper is not yet indexed on hf.co/papers. See Error handling for info.

Alternatively, you can request markdown from the normal paper page URL, like so:

curl -s -H "Accept: text/markdown" "https://huggingface.co/papers/{PAPER_ID}"

Paper Pages API Endpoints

All endpoints use the base URL https://huggingface.co.

Get structured metadata

Fetch the paper metadata as JSON using the Hugging Face REST API:

curl -s "https://huggingface.co/api/papers/{PAPER_ID}"

This returns structured metadata that can include:

  • authors (names and Hugging Face usernames, in case they have claimed the paper)
  • media URLs (uploaded when submitting the paper to Daily Papers)
  • summary (abstract) and AI-generated summary
  • project page and GitHub repository
  • organization and engagement metadata (number of upvotes)

To find models linked to the paper, use:

curl https://huggingface.co/api/models?filter=arxiv:{PAPER_ID}

To find datasets linked to the paper, use:

curl https://huggingface.co/api/datasets?filter=arxiv:{PAPER_ID}

To find spaces linked to the paper, use:

curl https://huggingface.co/api/spaces?filter=arxiv:{PAPER_ID}

Claim paper authorship

Claim authorship of a paper for a Hugging Face user:

curl "https://huggingface.co/api/settings/papers/claim" \
  --request POST \
  --header "Content-Type: application/json" \
  --header "Authorization: Bearer $HF_TOKEN" \
  --data '{
    "paperId": "{PAPER_ID}",
    "claimAuthorId": "{AUTHOR_ENTRY_ID}",
    "targetUserId": "{USER_ID}"
  }'
  • Endpoint: POST /api/settings/papers/claim
  • Body:

- paperId (string, required): arXiv paper identifier being claimed - claimAuthorId (string): author entry on the paper being claimed, 24-char hex ID - targetUserId (string): HF user who should receive the claim, 24-char hex ID

  • Response: paper authorship claim result, including the claimed paper ID

Get daily papers

Fetch the Daily Papers feed:

curl -s -H "Authorization: Bearer $HF_TOKEN" \
  "https://huggingface.co/api/daily_papers?p=0&limit=20&date=2017-07-21&sort=publishedAt"
  • Endpoint: GET /api/daily_papers
  • Query parameters:

- p (integer): page number - limit (integer): number of results, between 1 and 100 - date (string): RFC 3339 full-date, for example 2017-07-21 - week (string): ISO week, for example 2024-W03 - month (string): month value, for example 2024-01 - submitter (string): filter by submitter - sort (enum): publishedAt or trending

  • Response: list of daily papers

List papers

List arXiv papers sorted by published date:

curl -s -H "Authorization: Bearer $HF_TOKEN" \
  "https://huggingface.co/api/papers?cursor={CURSOR}&limit=20"
  • Endpoint: GET /api/papers
  • Query parameters:

- cursor (string): pagination cursor - limit (integer): number of results, between 1 and 100

  • Response: list of papers

Search papers

Perform hybrid semantic and full-text search on papers:

curl -s -H "Authorization: Bearer $HF_TOKEN" \
  "https://huggingface.co/api/papers/search?q=vision+language&limit=20"

This searches over the paper title, authors, and content.

  • Endpoint: GET /api/papers/search
  • Query parameters:

- q (string): search query, max length 250 - limit (integer): number of results, between 1 and 120

  • Response: matching papers

Index a paper

Insert a paper from arXiv by ID. If the paper is already indexed, only its authors can re-index it:

curl "https://huggingface.co/api/papers/index" \
  --request POST \
  --header "Content-Type: application/json" \
  --header "Authorization: Bearer $HF_TOKEN" \
  --data '{
    "arxivId": "{ARXIV_ID}"
  }'
  • Endpoint: POST /api/papers/index
  • Body:

- arxivId (string, required): arXiv ID to index, for example 2301.00001

  • Pattern: ^\d{4}\.\d{4,5}$
  • Response: empty JSON object on success

Update paper links

Update the project page, GitHub repository, or submitting organization for a paper. The requester must be the paper author, the Daily Papers submitter, or a papers admin:

curl "https://huggingface.co/api/papers/{PAPER_OBJECT_ID}/links" \
  --request POST \
  --header "Content-Type: application/json" \
  --header "Authorization: Bearer $HF_TOKEN" \
  --data '{
    "projectPage": "https://example.com",
    "githubRepo": "https://github.com/org/repo",
    "organizationId": "{ORGANIZATION_ID}"
  }'
  • Endpoint: POST /api/papers/{paperId}/links
  • Path parameters:

- paperId (string, required): Hugging Face paper object ID

  • Body:

- githubRepo (string, nullable): GitHub repository URL - organizationId (string, nullable): organization ID, 24-char hex ID - projectPage (string, nullable): project page URL

  • Response: empty JSON object on success

Error Handling

  • 404 on https://huggingface.co/papers/{PAPER_ID} or md endpoint: the paper is not indexed on Hugging Face paper pages yet.
  • 404 on /api/papers/{PAPER_ID}: the paper may not be indexed on Hugging Face paper pages yet.
  • Paper ID not found: verify the extracted arXiv ID, including any version suffix

Fallbacks

If the Hugging Face paper page does not contain enough detail for the user's question:

  • Check the regular paper page at https://huggingface.co/papers/{PAPER_ID}
  • Fall back to the arXiv page or PDF for the original source:

- https://arxiv.org/abs/{PAPER_ID} - https://arxiv.org/pdf/{PAPER_ID}

Notes

  • No authentication is required for public paper pages.
  • Write endpoints such as claim authorship, index paper, and update paper links require Authorization: Bearer $HF_TOKEN.
  • Prefer the .md endpoint for reliable machine-readable output.
  • Prefer /api/papers/{PAPER_ID} when you need structured JSON fields instead of page markdown.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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。

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可疑

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。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。

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