Official agent skill

Hugging Face Paper Pages

by huggingface in huggingface/skills

Fetches Hugging Face paper pages as markdown and reads paper metadata through the papers API when you share a paper URL, an arXiv link or an arXiv ID.

OfficialApache-2.0Auto-check passedResearch & Science

Install Hugging Face Paper Pages

skills CLI
$ npx skills add huggingface/skills --skill huggingface-papers -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install huggingface/skills huggingface-papers --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/huggingface/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/huggingface-papers .claude/skills/huggingface-papers && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
huggingface-papers
GitHub stars
11k
Used in
3 other repos
Token cost
~2.3k tokens
SKILL.md length
1,000 words
Files
1
Skills in repo
25
Repo updated
First seen
Licence
Apache-2.0

At a glance

Fetches Hugging Face paper pages as markdown and reads paper metadata through the papers API when you share a paper URL, an arXiv link or an arXiv ID.

  • Summarizing a paper from a Hugging Face paper page or arXiv link
  • SKILL.md covers When to Use, Parsing the paper ID, Error Handling and Notes
  • Calls curl; reaches huggingface.co and arxiv.org; needs HF_TOKEN
  • Finding the models, datasets and Spaces linked to a research paper

What it does

Hugging Face paper pages are a layer over arXiv for AI and computer science research, and this skill teaches the agent to read them. It parses the paper ID from whatever you hand over, whether a `huggingface.co/papers` URL, its `.md` form, an arXiv abs or pdf link or a bare ID such as `2602.08025v1`, and then calls the papers API.

Paper content can be fetched as markdown, and structured metadata comes back too: authors, linked models, datasets and Spaces, the GitHub repository and the project page. Background notes explain how authors claim a paper and link checkpoints by mentioning the paper URL in a model card, dataset card or Space README, and that submission to Daily Papers is possible only within 14 days of the arXiv publication date. Use it to summarize, explain or analyze a paper.

When your agent uses it

  • Summarizing a paper from a Hugging Face paper page or arXiv link
  • Finding the models, datasets and Spaces linked to a research paper
  • Looking up a paper's authors, GitHub repo or project page

Example prompts

  • “Summarize https://huggingface.co/papers/2602.08025 for me.”
  • “Which models and datasets are linked to arXiv paper 2602.08025?”
  • “Explain the method in https://arxiv.org/abs/2602.08025 in plain terms.”

Requirements

  • Network access to huggingface.co

What it can do on your machine

Read from SKILL.md and the folder at commit ca0325b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • curl

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • huggingface.co
    • arxiv.org
    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • HF_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Hugging Face Paper Pages loads about 2.3k tokens when it runs. Until then it costs about 85 tokens; SKILL.md has 1,000 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~85
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from huggingface/skills at commit ca0325b, republished under its Apache-2.0 licence (© huggingface). 1,000 words, ~2,337 tokens.

Download SKILL.mdSave it as .claude/skills/huggingface-papers/SKILL.md (or your agent's skills folder).
name
huggingface-papers
description
Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.

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:

bash
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:

bash
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:

bash
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:

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

To find datasets linked to the paper, use:

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

To find spaces linked to the paper, use:

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

Claim authorship of a paper for a Hugging Face user:

bash
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
Show full SKILL.md (380 more words)Show less
Get daily papers

Fetch the Daily Papers feed:

bash
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:

bash
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:

bash
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:

bash
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 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:

bash
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.

© huggingface, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/huggingface-papers of huggingface/skills.

Open the folder on GitHubat commit ca0325b

Used in 3 other repositories

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in huggingface/skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Morning AIdavepoon/buildwithclaude3.6k1 repos~405Automated safety check: PassMIT
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Questions about Hugging Face Paper Pages

What does Hugging Face Paper Pages do?

Fetches Hugging Face paper pages as markdown and reads paper metadata through the papers API when you share a paper URL, an arXiv link or an arXiv ID. Hugging Face paper pages are a layer over arXiv for AI and computer science research, and this skill teaches the agent to read them.08025v1`, and then calls the papers API.

When should I use Hugging Face Paper Pages?

Hugging Face Paper Pages fits situations like: summarizing a paper from a Hugging Face paper page or arXiv link; finding the models, datasets and Spaces linked to a research paper; looking up a paper's authors, GitHub repo or project page.

How do I install Hugging Face Paper Pages in Claude Code?

Run `npx skills add huggingface/skills --skill huggingface-papers -a claude-code`. Or copy the skill folder (skills/huggingface-papers in huggingface/skills) into .claude/skills/huggingface-papers in your project. Claude Code loads it when a task matches its description.

How do I install Hugging Face Paper Pages in Codex?

Run `npx skills add huggingface/skills --skill huggingface-papers -a codex`. Or copy the skill folder (skills/huggingface-papers in huggingface/skills) into .agents/skills/huggingface-papers in your project. Codex loads it when a task matches its description.

Can I use Hugging Face Paper Pages in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add huggingface/skills --skill huggingface-papers -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/huggingface-papers, .gemini/skills/huggingface-papers, .github/skills/huggingface-papers and .opencode/skills/huggingface-papers in your project.

What does Hugging Face Paper Pages need to run?

Going by SKILL.md and its folder, Hugging Face Paper Pages needs the command-line tools its instructions call (curl) and credentials named HF_TOKEN. Our summary lists: Network access to huggingface.co.

Does Hugging Face Paper Pages access the network?

SKILL.md names 3 domains. In commands or code: huggingface.co, arxiv.org and github.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Hugging Face Paper Pages safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Hugging Face Paper Pages use?

Hugging Face Paper Pages is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Hugging Face Paper Pages use?

About 2.3k tokens (SKILL.md is roughly 9.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Hugging Face Paper Pages?

Skills that share tags, products or a category with Hugging Face Paper Pages: News Aggregator Skill (cclank/news-aggregator-skill, 1.3k stars), Ideer Daily Paper (AI45Lab/iDeer, 416 stars), Morning AI (davepoon/buildwithclaude, 3.6k stars) and Phyai Model Arch Research (mingti-org/phyai, 128 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Hugging Face Paper Pages?

huggingface (a GitHub organization, an official publisher) maintains it in huggingface/skills, which has 11,142 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on October 1, 2026.

Source: huggingface/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.