Skill: lifei68801/arxiv-digest (version 1.0.1)

--- name: arxiv-digest version: 1.0.1 description: "Daily AI/ML paper digest from HuggingFace Papers Trending with accessible interpretations. Fetch trending papers from arXiv, provide plain-language summaries, and support automated daily delivery. Use when: (1) asking for latest AI/ML papers or arxiv research (2) setting up paper digest notifications (3) explaining research in simple terms. Triggers on: arxiv, papers, 论文, trending, research news, 热门论文, latest papers, paper digest." license: MIT-0 author: lifei68801 metadata: openclaw: requires: bins: ["python3"] pypi: ["requests"] permissions: - "net:fetch:huggingface.co/papers/*" behavior: networkAccess: true modifiesLocalFiles: true description: "Fetches trending papers from HuggingFace Papers API. Stores history locally for deduplication. No authentication required. No sensitive data transmission." initQuestions: - id: digest_time question: "What time should we deliver the daily digest? (Beijing time)" type: time default: "12:00" - id: categories question: "Which arXiv categories to follow? (comma-separated)" type: text default: "cs.AI,cs.CL,cs.LG" hint: "Popular: cs.AI(AI), cs.CL(NLP), cs.LG(ML), cs.CV(Vision), cs.RO(Robotics)" - id: paper_limit question: "How many papers per digest?" type: number default: 5 min: 1 max: 20 - id: language question: "Language for paper interpretations?" type: select default: "zh" options: - value: zh label: 中文 - value: en label: English --- # arXiv Paper Digest Daily AI/ML trending papers with accessible interpretations. Never miss important research again. ## What It Does - **Fetch trending papers** from HuggingFace Papers Trending (real-time hot papers) - **Smart ranking** by combining trending position, upvotes, and freshness - **Plain-language summaries** - one-sentence takeaways, key innovations, why it matters - **Automated delivery** via cron - daily QQ/Notion push - **Deduplication** - tracks history, no repeats --- ## Quick Start ### Check Dependencies ```bash python3 --version && curl --version ``` ### Basic Usage ```bash # Today's top 5 trending AI papers (Chinese) python3 scripts/fetch_papers.py --days 1 --limit 5 --lang zh # Custom categories python3 scripts/fetch_papers.py --category cs.AI --category cs.CV --days 7 --limit 10 # Markdown output python3 scripts/fetch_papers.py --days 1 --limit 5 --output markdown ``` ### In OpenClaw Agent Just say: > "今天有什么热门 AI 论文" The agent will automatically: 1. Fetch trending papers from HuggingFace 2. Rank by combined score 3. Generate accessible summaries --- ## Commands Reference | Command | Description | |---------|-------------| | `python3 scripts/fetch_papers.py --days 1 --limit 5` | Today's top 5 papers | | `--category cs.AI --category cs.CL` | Custom categories | | `--days 7` | Last 7 days | | `--lang zh` | Chinese summaries (default) | | `--lang en` | English summaries | | `--output json` | JSON format | | `--output markdown` | Markdown format | --- ## How It Works ### Ranking Algorithm Papers sorted by **combined score**: | Score Type | Range | Description | |------------|-------|-------------| | Position | 0-100 | Higher trending rank = higher score | | Upvote | 0-50 | More community votes = higher score | | Freshness | 0-30 | Newer papers get bonus | This ensures **both latest and hottest** papers surface. ### Processing Pipeline ``` HuggingFace Papers API ↓ Fetch Trending ↓ Score & Rank ↓ Deduplication (history file) ↓ Generate Summaries ↓ Output (JSON/Markdown) ``` --- ## Interpretation Template Each paper includes: ```markdown ### 📄 {Title} **One-sentence summary**: {Core contribution, <20 words} **Key innovations**: 1. {Technical breakthrough} 2. {Method improvement} **Plain-language explanation**: {200-300 words in everyday language} **Why it matters**: {50-100 words on practical significance} --- ``` --- ## Cron Integration Daily automated digest: ```json { "name": "arxiv-daily", "schedule": { "kind": "cron", "expr": "0 12 * * *", "tz": "Asia/Shanghai" }, "sessionTarget": "isolated", "wakeMode": "now", "payload": { "kind": "agentTurn", "message": "Use arxiv-digest skill. Fetch 5 papers, language zh. Push to QQ.", "deliver": true, "channel": "qqbot", "to": "YOUR_QQ_ID" } } ``` --- ## arXiv Categories | Code | Field | |------|-------| | cs.AI | Artificial Intelligence | | cs.CL | Natural Language Processing | | cs.LG | Machine Learning | | cs.CV | Computer Vision | | cs.RO | Robotics | | cs.NE | Neural Computing | | stat.ML | Statistical ML | Full list: https://arxiv.org/category_taxonomy --- ## File Structure ``` ~/.openclaw/workspace/skills/arxiv-digest/ ├── SKILL.md # This file ├── scripts/ │ └── fetch_papers.py # Main fetch script ├── references/ │ └── digest-guide.md # Interpretation patterns └── memory/history/ └── papers-trending-history.md # Deduplication history ``` --- ## Troubleshooting ### "No papers returned" - HuggingFace API may be slow - retry in a few seconds - Check network connectivity ### "Python module not found" ```bash pip install requests ``` ### "History file not found" First run creates it automatically at `memory/history/papers-trending-history.md` --- ## Changelog ### v1.0.1 (2026-03-12) - Security: Use requests library (preferred) to reduce false positives - Security: Simplify User-Agent header - Dependency: Added requests to pypi requirements - Fallback: Still supports urllib if requests not installed ### v1.0.0 (2026-03-12) - Initial release - HuggingFace Papers Trending integration - Combined score ranking (position + upvote + freshness) - Chinese/English output support - Deduplication history tracking --- *Stay on top of AI research. Read less, learn more.*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)