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antigravity-awesome-skills/skills/hugging-face-paper-publisher/SKILL.md
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---
source: "https://github.com/huggingface/skills/tree/main/skills/huggingface-paper-publisher"
name: hugging-face-paper-publisher
description: Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.
risk: unknown
source: https://github.com/huggingface/skills/tree/main/skills/huggingface-paper-publisher
source_repo: huggingface/skills
source_type: official
date_added: 2026-07-01
license: Apache-2.0
license_source: https://github.com/huggingface/skills/blob/main/LICENSE
---
# Overview
## When to Use
Use this skill when a user wants to publish, link, index, or manage research papers on the Hugging Face Hub.
Use this skill when you need publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.
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
@@ -629,6 +635,7 @@ Planned features for future versions:
- Paper metrics and impact tracking
## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
- Use this skill only when the task clearly matches its upstream product or API scope.
- Verify commands, API behavior, pricing, quotas, credentials, and deployment effects against current official documentation before making changes.
- Do not treat generated examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.