hugging-face daily papers

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

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

powershell

# 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

bash

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

text

📄 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