huggingface-papers

huggingface-papers is a skill for Codex from PracticalSwan/agent-skills. It costs 78 tokens per session (3,067 once invoked), scanned A, a copy of huggingface-papers, MIT.

A research-paper lookup tool for Hugging Face and arXiv pages. It reads papers and provides details such as authors, related models, datasets, code repositories, and project pages.

In plain words
What is it for?
Use it to summarize, explain, or analyze AI and computer-science papers, and to inspect the research connected to Hugging Face models or datasets.
Why use it?
It saves you from searching across separate paper pages, metadata listings, and linked project sites. It also helps explain or analyze an AI research paper from its URL or identifier.

Skill for Codex

Written for Codex: reads ~/.codex or $CODEX_HOME. Also seen: mentions Claude Code; mentions Codex.

Good fit Use it to summarize, explain, or analyze AI and computer-science papers, and to inspect the research connected to Hugging Face models or datasets.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/practicalswan/agent-skills/huggingface-papers
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add PracticalSwan/agent-skills --skill huggingface-papers
Clone the repo
git clone --depth 1 https://github.com/PracticalSwan/agent-skills

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for huggingface-papers

README.md
[![agentmods](https://agentmods.dev/badge/skills/practicalswan/agent-skills/huggingface-papers/github.svg)](https://agentmods.dev/skills/practicalswan/agent-skills/huggingface-papers)
Your own site
<a href="https://agentmods.dev/skills/practicalswan/agent-skills/huggingface-papers"><img src="https://agentmods.dev/badge/skills/practicalswan/agent-skills/huggingface-papers/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for huggingface-papers

Your own site · 80×15
<a href="https://agentmods.dev/skills/practicalswan/agent-skills/huggingface-papers"><img src="https://agentmods.dev/badge/skills/practicalswan/agent-skills/huggingface-papers.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 78 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,067 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin 88% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00078 $0.03067
Opus 5 $0.00039 $0.01533
Sonnet 5 $0.00016 $0.00613
Haiku 4.5 $0.00008 $0.00307

Measured 3d ago against content hash e5ba0f8010f4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

huggingface-papers scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

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

This is a copy

88% identical to huggingface-papers — 56 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

huggingface-papers/SKILL.md · 291 lines

How it starts

The opening of the file, as written. The whole thing — 291 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

Read the full file on GitHub · 291 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 3d ago Changed e5ba0f8010f4
  2. 4d ago Changed 2e5f637c47bf
  3. 7d ago First seen · 291 lines · 78 tokens per session scan A 2ee1c59ff71c

Subscribe to this mod's changes

huggingface-papers is a skill published in the GitHub repository PracticalSwan/agent-skills (14 stars, last pushed 3d ago), licensed MIT. It adds 78 tokens to every session and 3,067 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). It is 88% identical to huggingface-papers, differing in 56 lines, and is treated as a copy.