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Agent Skill · 研究检索

hugging-face-paper-publisher(拥抱面纸出版商)

hugging-face-paper-publisher 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

hugging-face-paper-publisher 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 62,606。

总安装 329周安装 14GitHub Stars 33,271下载 115核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:hugging-face-paper-publisher(拥抱面纸出版商)
来源仓库:https://github.com/patchy631/ai-engineering-hub
仓库路径:skills/hugging-face-paper-publisher
安装命令:
npx skills add https://github.com/patchy631/ai-engineering-hub --skill hugging-face-paper-publisher
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/patchy631/ai-engineering-hub --skill hugging-face-paper-publisher

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息。hugging-face-paper-publisher 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合在科研或文献调研中快速获取候选资料。通过 GitHub 安装,兼容多个 AI 工具链。建议确认原始 README 以了解具体用法。注意权限范围和潜在的文件读写行为。

来源仓库内路径:skills/hugging-face-paper-publisher

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/patchy631/ai-engineering-hub --skill hugging-f…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

hugging-face-paper-publisher 怎么安装?

在终端执行 npx skills add https://github.com/patchy631/ai-engineering-hub --skill hugging-face-paper-…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

hugging-face-paper-publisher 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

hugging-face-paper-publisher 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

hugging-face-paper-publisher 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

hugging-face-paper-publisher 用的人多吗?

公开数据是累计安装 329 次,近一周安装 14 次,下载 115 次,GitHub 33,271 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

hugging-face-paper-publisher 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 来源仓库有 33,271 星,维护活跃度相对可查。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
hugging-face-paper-publisher

拥抱面纸出版商 · 本页

32933,271接触敏感数据未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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

Usage Instructions

The skill includes Python scripts in scripts/ for paper publishing operations.

Prerequisites

  • Install dependencies: uv add huggingface_hub pyyaml requests markdown python-dotenv
  • Set HF_TOKEN environment variable with Write-access token
  • Activate virtual environment: source.venv/bin/activate

Method 1: Index Paper from arXiv

Add a paper to Hugging Face Paper Pages from arXiv.

Basic Usage:

python scripts/paper_manager.py index \
  --arxiv-id "2301.12345"

Check If Paper Exists:

python scripts/paper_manager.py check \
  --arxiv-id "2301.12345"

Direct URL Access: You can also visit https://huggingface.co/papers/{arxiv-id} directly to index a paper.

Method 2: Link Paper to Model/Dataset

Add paper references to model or dataset README with proper YAML metadata.

Add to Model Card:

python scripts/paper_manager.py link \
  --repo-id "username/model-name" \
  --repo-type "model" \
  --arxiv-id "2301.12345"

Add to Dataset Card:

python scripts/paper_manager.py link \
  --repo-id "username/dataset-name" \
  --repo-type "dataset" \
  --arxiv-id "2301.12345"

Add Multiple Papers:

python scripts/paper_manager.py link \
  --repo-id "username/model-name" \
  --repo-type "model" \
  --arxiv-ids "2301.12345,2302.67890,2303.11111"

With Custom Citation:

python scripts/paper_manager.py link \
  --repo-id "username/model-name" \
  --repo-type "model" \
  --arxiv-id "2301.12345" \
  --citation "$(cat citation.txt)"
How Linking Works

When you add an arXiv paper link to a model or dataset README:

  1. The Hub extracts the arXiv ID from the link
  2. A tag arxiv:<PAPER_ID> is automatically added to the repository
  3. Users can click the tag to view the Paper Page
  4. The Paper Page shows all models/datasets citing this paper
  5. Papers are discoverable through filters and search

Method 3: Claim Authorship

Verify your authorship on papers published on Hugging Face.

Start Claim Process:

python scripts/paper_manager.py claim \
  --arxiv-id "2301.12345" \
  --email "your.email@institution.edu"

Manual Process:

  1. Navigate to your paper's page: https://huggingface.co/papers/{arxiv-id}
  2. Find your name in the author list
  3. Click your name and select "Claim authorship"
  4. Wait for admin team verification

Check Authorship Status:

python scripts/paper_manager.py check-authorship \
  --arxiv-id "2301.12345"

Method 4: Manage Paper Visibility

Control which verified papers appear on your public profile.

List Your Papers:

python scripts/paper_manager.py list-my-papers

Toggle Visibility:

python scripts/paper_manager.py toggle-visibility \
  --arxiv-id "2301.12345" \
  --show true

Manage in Settings: Navigate to your account settings → Papers section to toggle "Show on profile" for each paper.

Method 5: Create Research Article

Generate a professional markdown-based research paper using modern templates.

Create from Template:

python scripts/paper_manager.py create \
  --template "standard" \
  --title "Your Paper Title" \
  --output "paper.md"

Available Templates:

  • standard - Traditional scientific paper structure
  • modern - Clean, web-friendly format inspired by Distill
  • arxiv - arXiv-style formatting
  • ml-report - Machine learning experiment report

Generate Complete Paper:

python scripts/paper_manager.py create \
  --template "modern" \
  --title "Fine-Tuning Large Language Models with LoRA" \
  --authors "Jane Doe, John Smith" \
  --abstract "$(cat abstract.txt)" \
  --output "paper.md"

Convert to HTML:

python scripts/paper_manager.py convert \
  --input "paper.md" \
  --output "paper.html" \
  --style "modern"

Paper Template Structure

Standard Research Paper Sections:

---
title: Your Paper Title
authors: Jane Doe, John Smith
affiliations: University X, Lab Y
date: 2025-01-15
arxiv: 2301.12345
tags: [machine-learning, nlp, fine-tuning]
---

# Abstract
Brief summary of the paper...

# 1. Introduction
Background and motivation...

# 2. Related Work
Previous research and context...

# 3. Methodology
Approach and implementation...

# 4. Experiments
Setup, datasets, and procedures...

# 5. Results
Findings and analysis...

# 6. Discussion
Interpretation and implications...

# 7. Conclusion
Summary and future work...

# References

Modern Template Features:

  • Dynamic table of contents
  • Responsive design for web viewing
  • Code syntax highlighting
  • Interactive figures and charts
  • Math equation rendering (LaTeX)
  • Citation management
  • Author affiliation linking

Commands Reference

Index Paper:

python scripts/paper_manager.py index --arxiv-id "2301.12345"

Link to Repository:

python scripts/paper_manager.py link \
  --repo-id "username/repo-name" \
  --repo-type "model|dataset|space" \
  --arxiv-id "2301.12345" \
  [--citation "Full citation text"] \
  [--create-pr]

Claim Authorship:

python scripts/paper_manager.py claim \
  --arxiv-id "2301.12345" \
  --email "your.email@edu"

Manage Visibility:

python scripts/paper_manager.py toggle-visibility \
  --arxiv-id "2301.12345" \
  --show true|false

Create Research Article:

python scripts/paper_manager.py create \
  --template "standard|modern|arxiv|ml-report" \
  --title "Paper Title" \
  [--authors "Author1, Author2"] \
  [--abstract "Abstract text"] \
  [--output "filename.md"]

Convert Markdown to HTML:

python scripts/paper_manager.py convert \
  --input "paper.md" \
  --output "paper.html" \
  [--style "modern|classic"]

Check Paper Status:

python scripts/paper_manager.py check --arxiv-id "2301.12345"

List Your Papers:

python scripts/paper_manager.py list-my-papers

Search Papers:

python scripts/paper_manager.py search --query "transformer attention"

YAML Metadata Format

When linking papers to models or datasets, proper YAML frontmatter is required:

Model Card Example:

---
language:
  - en
license: apache-2.0
tags:
  - text-generation
  - transformers
  - llm
library_name: transformers
---

# Model Name

This model is based on the approach described in [Our Paper](https://arxiv.org/abs/2301.12345).

## Citation

@article{doe2023paper, title={Your Paper Title}, author={Doe, Jane and Smith, John}, journal={arXiv preprint arXiv:2301.12345}, year={2023} }

Dataset Card Example:

---
language:
  - en
license: cc-by-4.0
task_categories:
  - text-generation
  - question-answering
size_categories:
  - 10K<n<100K
---

# Dataset Name

Dataset introduced in [Our Paper](https://arxiv.org/abs/2301.12345).

For more details, see the [paper page](https://huggingface.co/papers/2301.12345).

The Hub automatically extracts arXiv IDs from these links and creates arxiv:2301.12345 tags.

Integration Examples

Workflow 1: Publish New Research

# 1. Create research article
python scripts/paper_manager.py create \
  --template "modern" \
  --title "Novel Fine-Tuning Approach" \
  --output "paper.md"

# 2. Edit paper.md with your content

# 3. Submit to arXiv (external process)
# Upload to arxiv.org, get arXiv ID

# 4. Index on Hugging Face
python scripts/paper_manager.py index --arxiv-id "2301.12345"

# 5. Link to your model
python scripts/paper_manager.py link \
  --repo-id "your-username/your-model" \
  --repo-type "model" \
  --arxiv-id "2301.12345"

# 6. Claim authorship
python scripts/paper_manager.py claim \
  --arxiv-id "2301.12345" \
  --email "your.email@edu"

Workflow 2: Link Existing Paper

# 1. Check if paper exists
python scripts/paper_manager.py check --arxiv-id "2301.12345"

# 2. Index if needed
python scripts/paper_manager.py index --arxiv-id "2301.12345"

# 3. Link to multiple repositories
python scripts/paper_manager.py link \
  --repo-id "username/model-v1" \
  --repo-type "model" \
  --arxiv-id "2301.12345"

python scripts/paper_manager.py link \
  --repo-id "username/training-data" \
  --repo-type "dataset" \
  --arxiv-id "2301.12345"

python scripts/paper_manager.py link \
  --repo-id "username/demo-space" \
  --repo-type "space" \
  --arxiv-id "2301.12345"

Workflow 3: Update Model with Paper Reference

# 1. Get current README
huggingface-cli download username/model-name README.md

# 2. Add paper link
python scripts/paper_manager.py link \
  --repo-id "username/model-name" \
  --repo-type "model" \
  --arxiv-id "2301.12345" \
  --citation "Full citation for the paper"

# The script will:
# - Add YAML metadata if missing
# - Insert arXiv link in README
# - Add formatted citation
# - Preserve existing content

Best Practices

  1. Paper Indexing

- Index papers as soon as they're published on arXiv - Include full citation information in model/dataset cards - Use consistent paper references across related repositories

  1. Metadata Management

- Add YAML frontmatter to all model/dataset cards - Include proper licensing information - Tag with relevant task categories and domains

  1. Authorship

- Claim authorship on papers where you're listed as author - Use institutional email addresses for verification - Keep paper visibility settings updated

  1. Repository Linking

- Link papers to all relevant models, datasets, and Spaces - Include paper context in README descriptions - Add BibTeX citations for easy reference

  1. Research Articles

- Use templates consistently within projects - Include code and data links in papers - Generate web-friendly HTML versions for sharing

Advanced Usage

Batch Link Papers:

# Link multiple papers to one repository
for arxiv_id in "2301.12345" "2302.67890" "2303.11111"; do
  python scripts/paper_manager.py link \
    --repo-id "username/model-name" \
    --repo-type "model" \
    --arxiv-id "$arxiv_id"
done

Extract Paper Info:

# Get paper metadata from arXiv
python scripts/paper_manager.py info \
  --arxiv-id "2301.12345" \
  --format "json"

Generate Citation:

# Create BibTeX citation
python scripts/paper_manager.py citation \
  --arxiv-id "2301.12345" \
  --format "bibtex"

Validate Links:

# Check all paper links in a repository
python scripts/paper_manager.py validate \
  --repo-id "username/model-name" \
  --repo-type "model"

Error Handling

  • Paper Not Found: arXiv ID doesn't exist or isn't indexed yet
  • Permission Denied: HF_TOKEN lacks write access to repository
  • Invalid YAML: Malformed metadata in README frontmatter
  • Authorship Failed: Email doesn't match paper author records
  • Already Claimed: Another user has claimed authorship
  • Rate Limiting: Too many API requests in short time

Troubleshooting

Issue: "Paper not found on Hugging Face"

  • Solution: Visit hf.co/papers/{arxiv-id} to trigger indexing

Issue: "Authorship claim not verified"

  • Solution: Wait for admin review or contact HF support with proof

Issue: "arXiv tag not appearing"

  • Solution: Ensure README includes proper arXiv URL format

Issue: "Cannot link to repository"

  • Solution: Verify HF_TOKEN has write permissions

Issue: "Template rendering errors"

  • Solution: Check markdown syntax and YAML frontmatter format

Resources and References

Integration with tfrere's Research Template

This skill complements tfrere's research article template by providing:

  • Automated paper indexing workflows
  • Repository linking capabilities
  • Metadata management tools
  • Citation generation utilities

You can use tfrere's template for writing, then use this skill to publish and link the paper on Hugging Face Hub.

Common Patterns

Pattern 1: New Paper Publication

# Write → Publish → Index → Link
python scripts/paper_manager.py create --template modern --output paper.md
# (Submit to arXiv)
python scripts/paper_manager.py index --arxiv-id "2301.12345"
python scripts/paper_manager.py link --repo-id "user/model" --arxiv-id "2301.12345"

Pattern 2: Existing Paper Discovery

# Search → Check → Link
python scripts/paper_manager.py search --query "transformers"
python scripts/paper_manager.py check --arxiv-id "2301.12345"
python scripts/paper_manager.py link --repo-id "user/model" --arxiv-id "2301.12345"

Pattern 3: Author Portfolio Management

# Claim → Verify → Organize
python scripts/paper_manager.py claim --arxiv-id "2301.12345"
python scripts/paper_manager.py list-my-papers
python scripts/paper_manager.py toggle-visibility --arxiv-id "2301.12345" --show true

API Integration

Python Script Example:

from scripts.paper_manager import PaperManager

pm = PaperManager(hf_token="your_token")

# Index paper
pm.index_paper("2301.12345")

# Link to model
pm.link_paper(
    repo_id="username/model",
    repo_type="model",
    arxiv_id="2301.12345",
    citation="Full citation text"
)

# Check status
status = pm.check_paper("2301.12345")
print(status)

Future Enhancements

Planned features for future versions:

  • Support for non-arXiv papers (conference proceedings, journals)
  • Automatic citation formatting from DOI
  • Paper comparison and versioning tools
  • Collaborative paper writing features
  • Integration with LaTeX workflows
  • Automated figure and table extraction
  • Paper metrics and impact tracking

平台分布

Codex

36.79%
按下载量换算42

Claude

30.24%
按下载量换算35

Cursor

18.12%
按下载量换算21

Gemini CLI

8.17%
按下载量换算9

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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