hugging-face daily papers

通过 Python 脚本调用 HuggingFace API 拉取指定日期（默认昨天）的 Daily Papers 数据，保存为 JSON；再依据创新性、实用性、技术深度与趣味性四项评分，按必读、值得关注、可略读三档输出带点评的论文精选摘要。需配置 HF Token。

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最近更新 2026-05-11 17:38:55

分类：搜索依赖：代码执行 / 读写文件 / 第三方 API / 内部调用大模型应用场景：研究 / 摘要总结 / 报告撰写 / 推荐

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add hf-daily-papers

Metadata

name: hf-daily-papers
description: Fetch and digest HuggingFace Daily Papers. Use when user asks for today's HF papers, daily paper digest, wants a paper report, or says 论文精选/今日论文/HF daily papers. Fetches from hf.co/papers via HF API, reads results, scores and generates a formatted digest with commentary.

HF Daily Papers

Fetch papers from HuggingFace Daily Papers feed and generate a digest with analysis.

Setup: Get Your HF Token

Go to https://huggingface.co/settings/tokens
Create a Read token (any name)
Set the token as an environment variable:

# Windows PowerShell
$env:HF_TOKEN = "hf_xxxxxxxxxxxxx"

# macOS / Linux / Git Bash
export HF_TOKEN="hf_xxxxxxxxxxxxx"

The script reads HF_TOKEN from os.environ. If not set, it exits with a clear error message.

Step 1: Run the fetcher

cd <skill-path>/scripts && python hf_papers.py [date YYYY-MM-DD]

No date arg = yesterday
Output: hf_results.json (saved in the working directory)

Step 2: Read results

Read hf_results.json. Fields:

Field	Description
`paperId`	arXiv ID
`title`	Paper title
`votes`	Community upvotes
`submittedBy`	Submitter name
`organization`	Research institution
`summary`	Full abstract (cleaned, up to 2000 chars)
`aiSummary`	AI-generated summary (200-300 chars, from HF blue box)
`githubRepo`	GitHub repo URL if available
`keywords`	AI-extracted keywords (up to 10)
`link`	HF paper page
`arxivLink`	arXiv abstract page

Step 3: Score and write digest

Scoring reference (10-point scale, intuition-based):

Dimension	Weight	Bonus signals
Innovation	0-3	New benchmark/dataset, novel direction, first-of-its-kind
Practicality	0-3	Has GitHub code, clear real-world application, big tech/academia
Technical depth	0-2	Summary >200 chars, contains RL/MCTS/evolutionary methods
Interestingness	0-2	Provocative thesis, cross-discipline, counterintuitive

High vote count (>10) is a bonus — reflects community heat.

Step 4: Output format

📄 HF Daily Papers · [date]  N papers total

## 🔴 Must Read (score 8-10)
[Title | ID | Organization
 Xiaolongxia comment: ...]
## 🟡 Worth Noting (score 6-7)
[Compact list + one-line evaluation]
## 🟢 Skim If Interested
[Ultra brief list]

## 🦞 Summary
Top 3 + today's main theme observations

Commentary guidelines:

Every "Must Read" paper needs a "Xiaolongxia comment" — explain the core insight in your own words
Say why it's worth reading and what makes it special
Can connect to other papers or industry trends
Tone: casual, witty, friendly — like chatting with a friend
"Worth Noting" entries: one sentence max