Huggingface Papers

Hugging FaceOfficialPublished by Hugging Face

Skill
Tool integration
Data and AI
Apache-2.0
Low risk

From the author

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.

— the description by Hugging Face

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill enables an agent to interact with the Hugging Face Papers platform, which serves as a hub for AI and computer science research papers indexed from arXiv. It provides capabilities to fetch paper content in markdown format, retrieve structured metadata (such as authors, linked models, datasets, and project repositories), and perform administrative tasks like indexing new papers or claiming authorship. The skill is designed to handle various input formats, including arXiv IDs and direct Hugging Face paper URLs, facilitating seamless integration between AI research documentation and the broader Hugging Face ecosystem.

What it does

Fetches research paper content in markdown format for easy reading and analysis.
Retrieves structured metadata including authors, project pages, and GitHub repositories.
Identifies and links associated models, datasets, and Spaces related to a specific paper.
Supports searching and listing papers via the Hugging Face API.
Allows authorized users to index new papers or update existing paper links.
Enables authorship claims for papers on the Hugging Face platform.

When to use it

When a user provides an arXiv ID or a link to a Hugging Face paper page.
When you need to summarize or explain the technical details of an AI research paper.
When you need to find code, datasets, or demo spaces associated with a specific research paper.
When performing research or literature reviews on AI topics using the Hugging Face ecosystem.

Advantages

Provides direct access to structured, machine-readable paper metadata.
Simplifies the process of finding related implementation artifacts like models and datasets.
Offers a standardized way to parse and extract information from diverse arXiv and HF sources.
Facilitates administrative management of paper metadata for authors and contributors.

Usage examples

“Can you summarize the main contributions of the paper with ID 2602.08025?”: The agent retrieves the paper's markdown content and provides a concise summary of its key findings and methodology.
“Find the GitHub repository and any associated datasets for the paper at https://huggingface.co/papers/2602.08025.”: The agent queries the API to extract the linked GitHub URL and lists any datasets tagged with the corresponding arXiv ID.

Install

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/huggingface/huggingface-papers/download

Unzip it into the cross-client skills folder of your project:

mkdir -p .agents/skills && unzip huggingface-papers.zip -d .agents/skills

Documentation by Hugging Face

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:

Input	Paper ID
`https://huggingface.co/papers/2602.08025`	`2602.08025`
`https://huggingface.co/papers/2602.08025.md`	`2602.08025`
`https://arxiv.org/abs/2602.08025`	`2602.08025`
`https://arxiv.org/pdf/2602.08025`	`2602.08025`
`2602.08025v1`	`2602.08025v1`
`2602.08025`	`2602.08025`

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.

Files

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Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

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Attribution and licence

Published by

Hugging Face

Publisher

Hugging Face (Official)

Source

huggingface/skills · skills/huggingface-papers · commit 25910b3

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Apache License 2.0 (redistribution allowed)

LICENSE (added by AutoGineer from LICENSE)
ATTRIBUTION.md (written by AutoGineer)

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2026-11-08

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