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.
npx skills add eugenepyvovarov/mcpbundler-agent-skills-marketplace --skill hugging-face-paper-publishergit clone --depth 1 https://github.com/eugenepyvovarov/mcpbundler-agent-skills-marketplaceWrote 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.
[](https://agentmods.dev/skills/eugenepyvovarov/mcpbundler-agent-skills-marketplace/hugging-face-paper-publisher)<a href="https://agentmods.dev/skills/eugenepyvovarov/mcpbundler-agent-skills-marketplace/hugging-face-paper-publisher"><img src="https://agentmods.dev/badge/skills/eugenepyvovarov/mcpbundler-agent-skills-marketplace/hugging-face-paper-publisher/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.
<a href="https://agentmods.dev/skills/eugenepyvovarov/mcpbundler-agent-skills-marketplace/hugging-face-paper-publisher"><img src="https://agentmods.dev/badge/skills/eugenepyvovarov/mcpbundler-agent-skills-marketplace/hugging-face-paper-publisher.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00042 | $0.04351 |
| Opus 5 | $0.00021 | $0.02176 |
| Sonnet 5 | $0.00008 | $0.00870 |
| Haiku 4.5 | $0.00004 | $0.00435 |
Grade A, and why
hugging-face-paper-publisher scanned grade A with 0 findings 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 12d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
97% identical to hugging-face-paper-publisher — 1,238 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.
How it starts
The opening of the file, as written. The whole thing — 623 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Overview
This skill provides comprehensive tools for AI engineers and researchers to publish, manage, and link research papers on the Hugging Face Hub. It streamlines the workflow from paper creation to publication, including integration with arXiv, model/dataset linking, and authorship management.
Integration with HF Ecosystem
- Paper Pages: Index and discover papers on Hugging Face Hub
- arXiv Integration: Automatic paper indexing from arXiv IDs
- Model/Dataset Linking: Connect papers to relevant artifacts through metadata
- Authorship Verification: Claim and verify paper authorship
- Research Article Template: Generate professional, modern scientific papers
Version
1.0.0
Dependencies
- huggingface_hub>=0.26.0
- pyyaml>=6.0.3
- requests>=2.32.5
- markdown>=3.5.0
- python-dotenv>=1.2.1
Core Capabilities
1. Paper Page Management
- Index Papers: Add papers to Hugging Face from arXiv
- Claim Authorship: Verify and claim authorship on published papers
- Manage Visibility: Control which papers appear on your profile
- Paper Discovery: Find and explore papers in the HF ecosystem
2. Link Papers to Artifacts
- Model Cards: Add paper citations to model metadata
- Dataset Cards: Link papers to datasets via README
- Automatic Tagging: Hub auto-generates arxiv:<PAPER_ID> tags
- Citation Management: Maintain proper attribution and references
3. Research Article Creation
- Markdown Templates: Generate professional paper formatting
- Modern Design: Clean, readable research article layouts
- Dynamic TOC: Automatic table of contents generation
- Section Structure: Standard scientific paper organization
- LaTeX Math: Support for equations and technical notation
4. Metadata Management
- YAML Frontmatter: Proper model/dataset card metadata
- Citation Tracking: Maintain paper references across repositories
- Version Control: Track paper updates and revisions
- Multi-Paper Support: Link multiple papers to single artifacts
What ships with it
7 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.
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.
- 12d ago First seen · 623 lines · 42 tokens per session scan A a9e12c89297d
hugging-face-paper-publisher is a skill published in the GitHub repository eugenepyvovarov/mcpbundler-agent-skills-marketplace (12 stars, last pushed 6mo ago), licensed MIT. It adds 42 tokens to every session and 4,351 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 97% identical to hugging-face-paper-publisher, differing in 1,238 lines, and is treated as a copy.
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