--- name: rss-paper-feeds description: "Set up RSS feeds and alerts to track new publications in your research area" metadata: openclaw: emoji: "🔔" category: "literature" subcategory: "discovery" keywords: ["RSS feed", "new publication tracking", "literature alert", "citation notification", "research monitoring"] source: "wentor" --- # RSS Paper Feeds A skill for configuring automated literature monitoring using RSS feeds, email alerts, and citation notifications. Stay current with new publications in your research area without manual searching. ## RSS Feed Sources for Academic Papers ### Journal-Level Feeds Most major publishers provide RSS feeds for their journals: | Publisher | Feed URL Pattern | Example | |-----------|-----------------|---------| | Nature | `https://www.nature.com/[journal].rss` | `nature.com/nature.rss` | | Science | `https://www.science.org/action/showFeed?type=etoc&feed=rss&jc=[code]` | jc=science | | Elsevier | `https://rss.sciencedirect.com/publication/science/[ISSN]` | ISSN 0004-3702 for AI | | Springer | `https://link.springer.com/search.rss?search-within=Journal&facet-journal-id=[id]` | id=10994 | | IEEE | `https://ieeexplore.ieee.org/rss/TOC[journal_number].XML` | | | arXiv | `https://rss.arxiv.org/rss/[category]` | cs.AI, stat.ML | ### Setting Up arXiv Feeds ```python import feedparser from datetime import datetime def fetch_arxiv_feed(categories: list[str], max_results: int = 50) -> list[dict]: """ Fetch recent papers from arXiv RSS feeds. Args: categories: List of arXiv categories (e.g., ['cs.AI', 'cs.CL', 'stat.ML']) max_results: Maximum number of papers to return """ all_papers = [] for category in categories: feed_url = f"https://rss.arxiv.org/rss/{category}" feed = feedparser.parse(feed_url) for entry in feed.entries[:max_results]: all_papers.append({ 'title': entry.title.strip(), 'authors': entry.get('author', 'Unknown'), 'abstract': entry.get('summary', '')[:500], 'link': entry.link, 'category': category, 'published': entry.get('published', ''), 'arxiv_id': entry.link.split('/')[-1] if entry.link else '' }) # Deduplicate (papers may appear in multiple categories) seen = set() unique = [] for p in all_papers: if p['arxiv_id'] not in seen: seen.add(p['arxiv_id']) unique.append(p) return unique[:max_results] # Example: monitor AI and NLP papers papers = fetch_arxiv_feed(['cs.AI', 'cs.CL', 'cs.LG'], max_results=30) for p in papers[:5]: print(f"[{p['category']}] {p['title']}") print(f" {p['link']}\n") ``` ## Citation Alerts ### Google Scholar Citations Alert ``` Setup: 1. Search for your key reference papers on Google Scholar 2. Click the "Cited by N" link under each paper 3. Click the envelope icon ("Create alert") at the top of results 4. Enter your email address 5. You will receive notifications when new papers cite that work Recommended: Set alerts for: - Your own publications (track who cites you) - 5-10 foundational papers in your field - Key competitor or collaborator publications ``` ### OpenAlex Citation Tracking ```python import requests def track_citations_openalex(work_id: str) -> dict: """ Monitor citations for a specific paper via OpenAlex. Args: work_id: OpenAlex work ID (e.g., 'W2741809807') or DOI """ headers = {"User-Agent": "ResearchPlugins/1.0 (https://wentor.ai)"} response = requests.get( f"https://api.openalex.org/works/{work_id}", headers=headers ) data = response.json() # Get recent citing works citing_resp = requests.get( "https://api.openalex.org/works", params={"filter": f"cites:{work_id}", "sort": "publication_date:desc", "per_page": 10}, headers=headers ) citing = citing_resp.json().get("results", []) return { 'paper': data.get('title', ''), 'current_citations': data.get('cited_by_count', 0), 'recent_citing_works': [ {'title': c.get('title'), 'year': c.get('publication_year')} for c in citing ], 'status': 'configured' } ``` ## RSS Reader Configuration ### Recommended RSS Readers for Researchers | Reader | Platform | Features | Cost | |--------|----------|----------|------| | Feedly | Web/mobile | AI summaries, boards, teams | Free tier + Pro $8/mo | | Inoreader | Web/mobile | Rules, filters, monitoring | Free tier + Pro $5/mo | | Zotero RSS | Desktop | Integrated with reference manager | Free | | Thunderbird | Desktop | Email + RSS in one client | Free | | Miniflux | Self-hosted | Minimal, fast, API | Free (self-hosted) | ### Organizing Feeds Effectively ```yaml feed_organization: folders: core_journals: description: "Top journals in my primary field" feeds: 5-8 check_frequency: "daily" broad_monitoring: description: "Adjacent fields and high-impact general journals" feeds: 10-15 check_frequency: "weekly" preprints: description: "arXiv categories and SSRN feeds" feeds: 3-5 check_frequency: "daily" citation_alerts: description: "New citations of key papers" feeds: 10-20 check_frequency: "weekly" workflow: daily: "Scan titles in core_journals and preprints (10 min)" weekly: "Review broad_monitoring and citation_alerts (30 min)" monthly: "Audit feed list, remove low-value feeds, add new ones" ``` ## Automated Filtering and Summarization ### Keyword-Based Paper Filtering ```python def filter_papers(papers: list[dict], keywords: list[str], title_weight: float = 3.0, abstract_weight: float = 1.0, threshold: float = 2.0) -> list[dict]: """ Score and filter papers by relevance to your research keywords. Args: papers: List of paper dicts with 'title' and 'abstract' keywords: Your research keywords title_weight: Weight multiplier for title matches abstract_weight: Weight multiplier for abstract matches threshold: Minimum relevance score to include """ scored = [] for paper in papers: score = 0 title_lower = paper.get('title', '').lower() abstract_lower = paper.get('abstract', '').lower() for kw in keywords: kw_lower = kw.lower() if kw_lower in title_lower: score += title_weight if kw_lower in abstract_lower: score += abstract_weight if score >= threshold: paper['relevance_score'] = score scored.append(paper) return sorted(scored, key=lambda x: x['relevance_score'], reverse=True) ``` ## Integration with Reference Managers Configure your RSS reader to send relevant papers directly to your reference manager (Zotero, Mendeley, or EndNote). Most readers support "Save to Zotero" browser extensions or IFTTT/Zapier integrations for automated workflows. This creates a seamless pipeline from discovery to organized storage. --- Source attribution: wentorai Original project: https://github.com/wentorai/research-plugins/blob/bf44b3cd617fa94c8a1b254c5d1987142ca3d631/skills/literature/discovery/rss-paper-feeds/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 Wentor AI Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: wentorai Original project: https://github.com/wentorai/research-plugins/blob/bf44b3cd617fa94c8a1b254c5d1987142ca3d631/skills/literature/discovery/rss-paper-feeds/SKILL.md Attribution basis: Source repository record Fields of work: Data & Analytics, Education & Research Roles: Academic Writer, Data Analyst, Researcher Specialties: API Tools: Feedparser, Requests Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 287e5e4d21773666cc767e542f66ad73f916757274f9389a19e5c9bc4959ff23