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Read and analyze Hugging Face paper pages or arXiv papers using markdown and the papers API metadata. USE WHEN you need to read, summarize, or pull metadata for an arXiv or HF paper.
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/Sheshiyer/skill-clusters --skill hugging-face-papers명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SKILL.md 표시 중
SOC 직업 분류 기준
| name | hugging-face-papers |
| description | Read and analyze Hugging Face paper pages or arXiv papers using markdown and the papers API metadata. USE WHEN you need to read, summarize, or pull metadata for an arXiv or HF paper. |
| cluster | ai-agents-meta |
| version | 1.0.0 |
| origin | antigravity-awesome-skills (MIT) |
| source | https://github.com/huggingface/skills/tree/main/skills/huggingface-papers |
| risk | unknown |
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:
authors field). This makes the paper page appear on their Hugging Face profile.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.
https://huggingface.co/papers/2602.08025)https://huggingface.co/papers/2602.08025.md)https://arxiv.org/abs/2602.08025 or https://arxiv.org/pdf/2602.08025)2602.08025)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.
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:
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}"
All endpoints use the base URL https://huggingface.co.
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:
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 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}"
}'
POST /api/settings/papers/claimpaperId (string, required): arXiv paper identifier being claimedclaimAuthorId (string): author entry on the paper being claimed, 24-char hex IDtargetUserId (string): HF user who should receive the claim, 24-char hex IDFetch 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"
GET /api/daily_papersp (integer): page numberlimit (integer): number of results, between 1 and 100date (string): RFC 3339 full-date, for example 2017-07-21week (string): ISO week, for example 2024-W03month (string): month value, for example 2024-01submitter (string): filter by submittersort (enum): publishedAt or trendingList arXiv papers sorted by published date:
curl -s -H "Authorization: Bearer $HF_TOKEN" \
"https://huggingface.co/api/papers?cursor={CURSOR}&limit=20"
GET /api/paperscursor (string): pagination cursorlimit (integer): number of results, between 1 and 100Perform 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.
GET /api/papers/searchq (string): search query, max length 250limit (integer): number of results, between 1 and 120Insert 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 $HF_TOKEN" \
--data '{
"arxivId": "{ARXIV_ID}"
}'
POST /api/papers/indexarxivId (string, required): arXiv ID to index, for example 2301.00001^\d{4}\.\d{4,5}$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}"
}'
POST /api/papers/{paperId}/linkspaperId (string, required): Hugging Face paper object IDgithubRepo (string, nullable): GitHub repository URLorganizationId (string, nullable): organization ID, 24-char hex IDprojectPage (string, nullable): project page URLhttps://huggingface.co/papers/{PAPER_ID} or md endpoint: the paper is not indexed on Hugging Face paper pages yet./api/papers/{PAPER_ID}: the paper may not be indexed on Hugging Face paper pages yet.If the Hugging Face paper page does not contain enough detail for the user's question:
https://huggingface.co/papers/{PAPER_ID}https://arxiv.org/abs/{PAPER_ID}https://arxiv.org/pdf/{PAPER_ID}Authorization: Bearer $HF_TOKEN..md endpoint for reliable machine-readable output./api/papers/{PAPER_ID} when you need structured JSON fields instead of page markdown.