huggingface-paper-publisher
by huggingfacehuggingface-paper-publisher helps publish and manage research papers on the Hugging Face Hub. Use it to index arXiv papers, link papers to models or datasets, verify authorship, and create markdown research articles with templates for technical writing.
This skill scores 78/100, which means it is a solid listing candidate for directory users who want Hugging Face paper publishing and linking workflows. The repository shows a real, executable workflow with commands, examples, templates, and a supporting script, so users can tell what it does and how to trigger it with less guesswork than a generic prompt.
- Clear, specific scope: publish and manage research papers on Hugging Face Hub, including arXiv indexing, model/dataset linking, and authorship handling.
- Operational evidence is strong: `scripts/paper_manager.py` plus quick-reference commands and worked examples show concrete invocation patterns.
- Good workflow support: multiple templates and example usage reduce setup ambiguity for paper creation and metadata linking.
- No install command in `SKILL.md`, so users may need to infer setup from the script and dependency notes.
- The repository excerpt shows some command coverage, but edge-case behavior, authentication requirements, and failure modes are not fully surfaced in the directory-facing docs.
Overview of huggingface-paper-publisher skill
What huggingface-paper-publisher does
The huggingface-paper-publisher skill helps you publish, manage, and connect research papers on the Hugging Face Hub. It is best for researchers, AI engineers, and technical writers who want a repeatable way to turn paper metadata or an arXiv ID into a discoverable Hub page, linked model/dataset references, or a polished markdown research article.
When this skill is the right fit
Use the huggingface-paper-publisher skill when your task is more than drafting a paper summary. It is useful if you need to index an existing arXiv paper, claim or verify authorship, attach paper citations to a model or dataset card, or generate a structured paper template for a technical writing workflow.
What makes it different
Unlike a generic prompt, this skill is built around Hugging Face Hub actions and supporting scripts. The repo includes a paper manager script, quick reference commands, and multiple templates, so the huggingface-paper-publisher install gives you a workflow-oriented starting point rather than a blank writing prompt.
How to Use huggingface-paper-publisher skill
Install and load the right files
For a huggingface-paper-publisher install, add the skill with:
npx skills add huggingface/skills --skill huggingface-paper-publisher
After installing, read SKILL.md first, then references/quick_reference.md, examples/example_usage.md, and scripts/paper_manager.py. If you plan to generate a paper draft, inspect the relevant template in templates/ before writing your prompt.
Give the skill complete source inputs
The skill works best when you provide a concrete goal, not just “publish my paper.” State the action, artifact type, and identifiers you already have. Strong inputs look like: “Index arXiv paper 2301.12345 and link it to username/my-model” or “Create a modern paper markdown draft from this abstract, authors list, and title.” This improves huggingface-paper-publisher usage because the workflow depends on exact repo IDs, arXiv IDs, and template choice.
Use a workflow, not a one-shot prompt
A practical huggingface-paper-publisher guide is: identify the paper, check whether it already exists, index or update it, then link it to models or datasets, and finally generate or refine the article content. For technical writing, choose the template first (standard, modern, arxiv, or ml-report) so the output structure matches your publication target.
Prefer the command examples as your starting point
The repo’s script expects uv run scripts/paper_manager.py ..., and the dependencies are designed around that path. Start from check, index, link, info, or create commands in the quick reference, then adapt the arguments to your repository. If you are unsure which step comes next, the example usage file is the fastest way to see the intended sequence.
huggingface-paper-publisher skill FAQ
Is huggingface-paper-publisher only for arXiv papers?
No. arXiv indexing is a core use case, but the skill also supports linking papers to Hugging Face models and datasets, and creating markdown-based research articles from templates. If your main job is “make my research visible and connected on the Hub,” this skill is a good fit.
Do I need to be a developer to use it?
Not necessarily, but you do need enough comfort with repo IDs, arXiv IDs, and command-line workflows to supply accurate inputs. Beginners can use the huggingface-paper-publisher skill successfully if they start with the quick reference and avoid trying to invent the whole publication flow from scratch.
Why use this instead of a normal prompt?
A normal prompt can draft a summary, but it usually cannot guide the full Hugging Face publication workflow as reliably. The huggingface-paper-publisher skill is better when correctness matters: matching IDs, choosing the right template, updating model or dataset cards, and keeping the output aligned with Hub conventions.
When should I not use it?
Skip this skill if you only need a plain-language summary, a literature review with no Hub publishing, or a non-Hugging Face article format. It is strongest when the end result is a Hub-facing paper page, linked artifact metadata, or a structured technical writing draft.
How to Improve huggingface-paper-publisher skill
Provide the missing publishing details up front
The most common reason huggingface-paper-publisher usage underperforms is incomplete input. Include the arXiv ID or title, target repo ID, repo type (model or dataset), author names, abstract, and the template you want. If claiming authorship or linking a paper, say whether the page already exists and whether the citation should be inserted into a README frontmatter block or body text.
Match the template to the output you want
For huggingface-paper-publisher for Technical Writing, template choice matters. Use modern for web-friendly presentation, arxiv for a paper-like layout, standard for straightforward academic structure, and ml-report for experiment reporting. If you want better results, ask the skill to preserve section order, keep headings literal, and avoid inventing sections not supported by the selected template.
Watch for common failure modes
The main issues are bad IDs, unclear target repos, and vague publication intent. If a paper should be indexed, say so explicitly; if a link should update a model card or dataset card, specify which one; if a draft should be generated, provide content that fills the template instead of asking for generic prose. These details help the skill avoid guessing.
Iterate on structure, then wording
After the first output, improve quality by requesting one focused revision: tighter abstract, clearer contribution bullets, cleaner citations, or better Hub-facing metadata. If the draft is meant for publication, review whether the article reads well as markdown in the Hub preview, then refine the section order and metadata before polishing style.