What does this skill do, and when should you use it?
This skill is for AI engineers and researchers who manage research outputs on the Hugging Face Hub. It indexes papers from arXiv, links them to models, datasets, and Spaces, supports authorship claims, and manages profile visibility. It also generates Markdown research articles from templates and converts them to HTML. It is a good fit for users already working in the Hugging Face ecosystem who want a repeatable paper-publication workflow.
It runs scripts/paper_manager.py with uv run to index or check papers by arXiv ID, search papers, link papers to model, dataset, or Space repositories, generate citations, start and check authorship claims, list a user's papers, and toggle profile visibility. It creates Markdown articles from the standard, modern, arxiv, and ml-report templates and converts Markdown to HTML. The scripts can read or update repository READMEs, YAML frontmatter, and paper links; Hugging Face Hub operations require an HF_TOKEN.
- A researcher indexes a newly published arXiv paper on Hugging Face Paper Pages.
- A model author adds a paper link and citation to a model card.
- A dataset maintainer connects one or more research papers to a dataset card.
- A listed author claims authorship and controls whether verified papers appear on their profile.
- An ML team generates a structured research article and a web-friendly HTML version from a template.
How do you install this skill?
- The link command uses HF_TOKEN to read and directly overwrite the target repository README; confirm the repository, permissions, and diff first, and keep a manual backup.
- Do not treat create-pr as a safe preview or pull-request mode; the source says it is unimplemented and still commits directly.
- Advertised features for visibility management, listing personal papers, and link validation have no corresponding implementation in the supplied script.
- index, search, and parts of the template functionality are weaker than described; external Hugging Face/arXiv availability and rate limits may affect results.
- Do not treat example metrics, authors, results, or citations in the templates as real research evidence.
- Shell / CLI
- Network access
- Local filesystem
uvhuggingface_hub>=0.26.0pyyaml>=6.0.3requests>=2.32.5markdown>=3.5.0python-dotenv>=1.2.1HF_TOKEN with write access
Following the repository README, copy or symlink skills/huggingface-paper-publisher into a standard Codex .agents/skills location, such as $REPO_ROOT/.agents/skills or $HOME/.agents/skills. The README also documents on-demand installation with hf skills add <skill-name>; for this skill, use hf skills add huggingface-paper-publisher.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/huggingface/skills.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/skills/huggingface-paper-publisher" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Once installed, send your agent any of these to trigger it:
- Use the Hugging Face paper publisher skill to index arXiv paper 2301.12345 and link it to username/model-name.
- Your Paper Title
Ask the coding agent something like “Use the Hugging Face paper publisher skill to index arXiv paper 2301.12345 and link it to username/model-name.” You can also run uv run scripts/paper_manager.py index --arxiv-id "2301.12345", link --repo-id "username/model-name" --repo-type "model" --arxiv-id "2301.12345", or create --template "modern" --title "Your Paper Title" --output "paper.md" from the skill directory. Set an HF_TOKEN with write access before running scripts; the source does not document the exact agent trigger behavior.
What are this skill's strengths and limitations?
- Covers indexing, repository linking, authorship, visibility, citation, and article-generation workflows.
- Supports model cards, dataset cards, Spaces, and multiple papers per artifact.
- Includes several paper templates, dynamic tables of contents, LaTeX math support, and HTML conversion.
- Uses PEP 723 inline dependencies and recommends `uv run` for execution.
- Requires network access to Hugging Face services and arXiv-related URLs, plus a write-capable token for publishing operations.
- Authorship claims may require administrator review and can fail when the email does not match author records.
- The source provides no test-suite, platform-coverage, or performance evidence.
- It does not replace the paper-writing process, and arXiv submission is described as an external step.
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| Hugging Face Paper Publisher this page | 36 · Not recommended | ★ 11k | 18d ago | Apache-2.0 |
| NeMo-RL Documentation Conventions ✓ NVIDIA · Official | 58 · Recommended | ★ 3.6k | 12d ago | Apache-2.0 |
| Blog Translate: SEO Blog Localization | 48 · Use with care | ★ 2.4k | 13d ago | MIT |
| Blog Voice Learner | 46 · Use with care | ★ 2.4k | 13d ago | MIT |
| Blog Rewrite Optimizer | 45 · Not recommended | ★ 2.4k | 13d ago | MIT |
How did FollowSkills review this skill?
The source requires HF_TOKEN and performs Hub reads and uploads, with linking defaulting to direct commits; it lacks user confirmation, least-privilege guidance, change preview, and rollback. The create-pr option still commits directly. Basic sanitization exists for external arXiv text, but token handling, data-flow disclosure, and provenance attribution are incomplete, so points are deducted.
The script includes input validation, exception handling, timeouts, and structured error returns, making the main paths statically plausible. However, documented commands such as list-my-papers, toggle-visibility, and validate are not implemented; search is only a placeholder, and dependency constraints do not match the documentation. No tests were executed, so the score remains low.
The intended scenarios are fairly clear: paper indexing, repository linking, and article templates. Trigger conditions, non-fit boundaries, output contracts, and permission prerequisites are underspecified. Core behavior depends on Hugging Face and arXiv services, with no mainland-China reachability assessment or Chinese-language support.
The skill has organized documentation, a quick reference, examples, templates, error handling, an Apache-2.0 repository license, and version 1.0.0. However, documentation and implementation diverge, while maintenance ownership, changelog, update path, and known limitations are not clearly stated; several templates remain placeholders. The unverified publisher identity is treated as unknown and is not independently penalized.
The code can plausibly perform some useful tasks: check papers, fetch arXiv metadata, edit repository READMEs, and generate drafts and BibTeX. But indexing does not actually perform indexing, several advertised features are absent, templates require substantial manual completion, and there is no static evidence of directly usable representative output or comparative benefit, warranting only a low score.
The committed script, examples, and return structures provide limited auditable evidence, but there is no committed test suite, CI coverage, or third-party execution evidence. Documentation conflicts with the implementation, so conclusions are limited to static inspection and cannot receive a higher score.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →