huggingface-papers
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.
Profile →npx skills add waybarrios/opencode-power-pack --skill huggingface-papers --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 ca
- When to Use
- Parsing the paper ID
- Fetch the paper page as markdown
- Paper Pages API Endpoints
- Error Handling
- Fallbacks
- Notes
curl -s "https://huggingface.co/papers/{PAPER_ID}.md"
curl -s -H "Accept: text/markdown" "https://huggingface.co/papers/{PAPER_ID}"
curl -s "https://huggingface.co/api/papers/{PAPER_ID}"
curl https://huggingface.co/api/models?filter=arxiv:{PAPER_ID}
curl https://huggingface.co/api/datasets?filter=arxiv:{PAPER_ID}
curl https://huggingface.co/api/spaces?filter=arxiv:{PAPER_ID}
curl "https://huggingface.co/api/settings/papers/claim" \
curl -s -H "Authorization: Bearer $HF_TOKEN" \
curl "https://huggingface.co/api/papers/index" \
curl "https://huggingface.co/api/papers/{PAPER_OBJECT_ID}/links" \What does the huggingface-papers skill do?
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.
How do I install it?
Run `npx skills add waybarrios/opencode-power-pack --skill huggingface-papers --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From waybarrios/opencode-power-pack, a repository with 443 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.