diff --git a/skills/research/DESCRIPTION.md b/skills/research/DESCRIPTION.md
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+---
+description: Skills for academic research, paper discovery, literature review, and scientific knowledge retrieval.
+---
diff --git a/skills/research/arxiv/SKILL.md b/skills/research/arxiv/SKILL.md
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+---
+name: arxiv
+description: Search and retrieve academic papers from arXiv using their free REST API. No API key needed. Search by keyword, author, category, or ID. Combine with web_extract or the ocr-and-documents skill to read full paper content.
+version: 1.0.0
+author: Hermes Agent
+license: MIT
+metadata:
+  hermes:
+    tags: [Research, Arxiv, Papers, Academic, Science, API]
+    related_skills: [ocr-and-documents]
+---
+
+# arXiv Research
+
+Search and retrieve academic papers from arXiv via their free REST API. No API key, no dependencies — just curl.
+
+## Quick Reference
+
+| Action | Command |
+|--------|---------|
+| Search papers | `curl "https://export.arxiv.org/api/query?search_query=all:QUERY&max_results=5"` |
+| Get specific paper | `curl "https://export.arxiv.org/api/query?id_list=2402.03300"` |
+| Read abstract (web) | `web_extract(urls=["https://arxiv.org/abs/2402.03300"])` |
+| Read full paper (PDF) | `web_extract(urls=["https://arxiv.org/pdf/2402.03300"])` |
+
+## Searching Papers
+
+The API returns Atom XML. Parse with `grep`/`sed` or pipe through `python3` for clean output.
+
+### Basic search
+
+```bash
+curl -s "https://export.arxiv.org/api/query?search_query=all:GRPO+reinforcement+learning&max_results=5"
+```
+
+### Clean output (parse XML to readable format)
+
+```bash
+curl -s "https://export.arxiv.org/api/query?search_query=all:GRPO+reinforcement+learning&max_results=5&sortBy=submittedDate&sortOrder=descending" | python3 -c "
+import sys, xml.etree.ElementTree as ET
+ns = {'a': 'http://www.w3.org/2005/Atom'}
+root = ET.parse(sys.stdin).getroot()
+for i, entry in enumerate(root.findall('a:entry', ns)):
+    title = entry.find('a:title', ns).text.strip().replace('\n', ' ')
+    arxiv_id = entry.find('a:id', ns).text.strip().split('/abs/')[-1]
+    published = entry.find('a:published', ns).text[:10]
+    authors = ', '.join(a.find('a:name', ns).text for a in entry.findall('a:author', ns))
+    summary = entry.find('a:summary', ns).text.strip()[:200]
+    cats = ', '.join(c.get('term') for c in entry.findall('a:category', ns))
+    print(f'{i+1}. [{arxiv_id}] {title}')
+    print(f'   Authors: {authors}')
+    print(f'   Published: {published} | Categories: {cats}')
+    print(f'   Abstract: {summary}...')
+    print(f'   PDF: https://arxiv.org/pdf/{arxiv_id}')
+    print()
+"
+```
+
+## Search Query Syntax
+
+| Prefix | Searches | Example |
+|--------|----------|---------|
+| `all:` | All fields | `all:transformer+attention` |
+| `ti:` | Title | `ti:large+language+models` |
+| `au:` | Author | `au:vaswani` |
+| `abs:` | Abstract | `abs:reinforcement+learning` |
+| `cat:` | Category | `cat:cs.AI` |
+| `co:` | Comment | `co:accepted+NeurIPS` |
+
+### Boolean operators
+
+```
+# AND (default when using +)
+search_query=all:transformer+attention
+
+# OR
+search_query=all:GPT+OR+all:BERT
+
+# AND NOT
+search_query=all:language+model+ANDNOT+all:vision
+
+# Exact phrase
+search_query=ti:"chain+of+thought"
+
+# Combined
+search_query=au:hinton+AND+cat:cs.LG
+```
+
+## Sort and Pagination
+
+| Parameter | Options |
+|-----------|---------|
+| `sortBy` | `relevance`, `lastUpdatedDate`, `submittedDate` |
+| `sortOrder` | `ascending`, `descending` |
+| `start` | Result offset (0-based) |
+| `max_results` | Number of results (default 10, max 30000) |
+
+```bash
+# Latest 10 papers in cs.AI
+curl -s "https://export.arxiv.org/api/query?search_query=cat:cs.AI&sortBy=submittedDate&sortOrder=descending&max_results=10"
+```
+
+## Fetching Specific Papers
+
+```bash
+# By arXiv ID
+curl -s "https://export.arxiv.org/api/query?id_list=2402.03300"
+
+# Multiple papers
+curl -s "https://export.arxiv.org/api/query?id_list=2402.03300,2401.12345,2403.00001"
+```
+
+## Reading Paper Content
+
+After finding a paper, read it:
+
+```
+# Abstract page (fast, metadata + abstract)
+web_extract(urls=["https://arxiv.org/abs/2402.03300"])
+
+# Full paper (PDF → markdown via Firecrawl)
+web_extract(urls=["https://arxiv.org/pdf/2402.03300"])
+```
+
+For local PDF processing, see the `ocr-and-documents` skill.
+
+## Common Categories
+
+| Category | Field |
+|----------|-------|
+| `cs.AI` | Artificial Intelligence |
+| `cs.CL` | Computation and Language (NLP) |
+| `cs.CV` | Computer Vision |
+| `cs.LG` | Machine Learning |
+| `cs.CR` | Cryptography and Security |
+| `stat.ML` | Machine Learning (Statistics) |
+| `math.OC` | Optimization and Control |
+| `physics.comp-ph` | Computational Physics |
+
+Full list: https://arxiv.org/category_taxonomy
+
+## Helper Script
+
+The `scripts/search_arxiv.py` script handles XML parsing and provides clean output:
+
+```bash
+python scripts/search_arxiv.py "GRPO reinforcement learning"
+python scripts/search_arxiv.py "transformer attention" --max 10 --sort date
+python scripts/search_arxiv.py --author "Yann LeCun" --max 5
+python scripts/search_arxiv.py --category cs.AI --sort date
+python scripts/search_arxiv.py --id 2402.03300
+python scripts/search_arxiv.py --id 2402.03300,2401.12345
+```
+
+No dependencies — uses only Python stdlib.
+
+---
+
+## Semantic Scholar (Citations, Related Papers, Author Profiles)
+
+arXiv doesn't provide citation data or recommendations. Use the **Semantic Scholar API** for that — free, no key needed for basic use (1 req/sec), returns JSON.
+
+### Get paper details + citations
+
+```bash
+# By arXiv ID
+curl -s "https://api.semanticscholar.org/graph/v1/paper/arXiv:2402.03300?fields=title,authors,citationCount,referenceCount,influentialCitationCount,year,abstract" | python3 -m json.tool
+
+# By Semantic Scholar paper ID or DOI
+curl -s "https://api.semanticscholar.org/graph/v1/paper/DOI:10.1234/example?fields=title,citationCount"
+```
+
+### Get citations OF a paper (who cited it)
+
+```bash
+curl -s "https://api.semanticscholar.org/graph/v1/paper/arXiv:2402.03300/citations?fields=title,authors,year,citationCount&limit=10" | python3 -m json.tool
+```
+
+### Get references FROM a paper (what it cites)
+
+```bash
+curl -s "https://api.semanticscholar.org/graph/v1/paper/arXiv:2402.03300/references?fields=title,authors,year,citationCount&limit=10" | python3 -m json.tool
+```
+
+### Search papers (alternative to arXiv search, returns JSON)
+
+```bash
+curl -s "https://api.semanticscholar.org/graph/v1/paper/search?query=GRPO+reinforcement+learning&limit=5&fields=title,authors,year,citationCount,externalIds" | python3 -m json.tool
+```
+
+### Get paper recommendations
+
+```bash
+curl -s -X POST "https://api.semanticscholar.org/recommendations/v1/papers/" \
+  -H "Content-Type: application/json" \
+  -d '{"positivePaperIds": ["arXiv:2402.03300"], "negativePaperIds": []}' | python3 -m json.tool
+```
+
+### Author profile
+
+```bash
+curl -s "https://api.semanticscholar.org/graph/v1/author/search?query=Yann+LeCun&fields=name,hIndex,citationCount,paperCount" | python3 -m json.tool
+```
+
+### Useful Semantic Scholar fields
+
+`title`, `authors`, `year`, `abstract`, `citationCount`, `referenceCount`, `influentialCitationCount`, `isOpenAccess`, `openAccessPdf`, `fieldsOfStudy`, `publicationVenue`, `externalIds` (contains arXiv ID, DOI, etc.)
+
+---
+
+## Complete Research Workflow
+
+1. **Discover**: `python scripts/search_arxiv.py "your topic" --sort date --max 10`
+2. **Assess impact**: `curl -s "https://api.semanticscholar.org/graph/v1/paper/arXiv:ID?fields=citationCount,influentialCitationCount"`
+3. **Read abstract**: `web_extract(urls=["https://arxiv.org/abs/ID"])`
+4. **Read full paper**: `web_extract(urls=["https://arxiv.org/pdf/ID"])`
+5. **Find related work**: `curl -s "https://api.semanticscholar.org/graph/v1/paper/arXiv:ID/references?fields=title,citationCount&limit=20"`
+6. **Get recommendations**: POST to Semantic Scholar recommendations endpoint
+7. **Track authors**: `curl -s "https://api.semanticscholar.org/graph/v1/author/search?query=NAME"`
+
+## Rate Limits
+
+| API | Rate | Auth |
+|-----|------|------|
+| arXiv | ~1 req / 3 seconds | None needed |
+| Semantic Scholar | 1 req / second | None (100/sec with API key) |
+
+## Notes
+
+- arXiv returns Atom XML — use the helper script or parsing snippet for clean output
+- Semantic Scholar returns JSON — pipe through `python3 -m json.tool` for readability
+- arXiv IDs: old format (`hep-th/0601001`) vs new (`2402.03300`)
+- PDF: `https://arxiv.org/pdf/{id}` — Abstract: `https://arxiv.org/abs/{id}`
+- HTML (when available): `https://arxiv.org/html/{id}`
+- For local PDF processing, see the `ocr-and-documents` skill
diff --git a/skills/research/arxiv/scripts/search_arxiv.py b/skills/research/arxiv/scripts/search_arxiv.py
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+#!/usr/bin/env python3
+"""Search arXiv and display results in a clean format.
+
+Usage:
+    python search_arxiv.py "GRPO reinforcement learning"
+    python search_arxiv.py "GRPO reinforcement learning" --max 10
+    python search_arxiv.py "GRPO reinforcement learning" --sort date
+    python search_arxiv.py --author "Yann LeCun" --max 5
+    python search_arxiv.py --category cs.AI --sort date --max 10
+    python search_arxiv.py --id 2402.03300
+    python search_arxiv.py --id 2402.03300,2401.12345
+"""
+import sys
+import urllib.request
+import urllib.parse
+import xml.etree.ElementTree as ET
+
+NS = {'a': 'http://www.w3.org/2005/Atom'}
+
+def search(query=None, author=None, category=None, ids=None, max_results=5, sort="relevance"):
+    params = {}
+    
+    if ids:
+        params['id_list'] = ids
+    else:
+        parts = []
+        if query:
+            parts.append(f'all:{urllib.parse.quote(query)}')
+        if author:
+            parts.append(f'au:{urllib.parse.quote(author)}')
+        if category:
+            parts.append(f'cat:{category}')
+        if not parts:
+            print("Error: provide a query, --author, --category, or --id")
+            sys.exit(1)
+        params['search_query'] = '+AND+'.join(parts)
+    
+    params['max_results'] = str(max_results)
+    
+    sort_map = {"relevance": "relevance", "date": "submittedDate", "updated": "lastUpdatedDate"}
+    params['sortBy'] = sort_map.get(sort, sort)
+    params['sortOrder'] = 'descending'
+    
+    url = "https://export.arxiv.org/api/query?" + "&".join(f"{k}={v}" for k, v in params.items())
+    
+    req = urllib.request.Request(url, headers={'User-Agent': 'HermesAgent/1.0'})
+    with urllib.request.urlopen(req, timeout=15) as resp:
+        data = resp.read()
+    
+    root = ET.fromstring(data)
+    entries = root.findall('a:entry', NS)
+    
+    if not entries:
+        print("No results found.")
+        return
+    
+    total = root.find('{http://a9.com/-/spec/opensearch/1.1/}totalResults')
+    if total is not None:
+        print(f"Found {total.text} results (showing {len(entries)})\n")
+    
+    for i, entry in enumerate(entries):
+        title = entry.find('a:title', NS).text.strip().replace('\n', ' ')
+        raw_id = entry.find('a:id', NS).text.strip()
+        arxiv_id = raw_id.split('/abs/')[-1].split('v')[0] if '/abs/' in raw_id else raw_id
+        published = entry.find('a:published', NS).text[:10]
+        updated = entry.find('a:updated', NS).text[:10]
+        authors = ', '.join(a.find('a:name', NS).text for a in entry.findall('a:author', NS))
+        summary = entry.find('a:summary', NS).text.strip().replace('\n', ' ')
+        cats = ', '.join(c.get('term') for c in entry.findall('a:category', NS))
+        
+        print(f"{i+1}. {title}")
+        print(f"   ID: {arxiv_id} | Published: {published} | Updated: {updated}")
+        print(f"   Authors: {authors}")
+        print(f"   Categories: {cats}")
+        print(f"   Abstract: {summary[:300]}{'...' if len(summary) > 300 else ''}")
+        print(f"   Links: https://arxiv.org/abs/{arxiv_id} | https://arxiv.org/pdf/{arxiv_id}")
+        print()
+
+
+if __name__ == "__main__":
+    args = sys.argv[1:]
+    if not args or args[0] in ("-h", "--help"):
+        print(__doc__)
+        sys.exit(0)
+    
+    query = None
+    author = None
+    category = None
+    ids = None
+    max_results = 5
+    sort = "relevance"
+    
+    i = 0
+    positional = []
+    while i < len(args):
+        if args[i] == "--max" and i + 1 < len(args):
+            max_results = int(args[i + 1]); i += 2
+        elif args[i] == "--sort" and i + 1 < len(args):
+            sort = args[i + 1]; i += 2
+        elif args[i] == "--author" and i + 1 < len(args):
+            author = args[i + 1]; i += 2
+        elif args[i] == "--category" and i + 1 < len(args):
+            category = args[i + 1]; i += 2
+        elif args[i] == "--id" and i + 1 < len(args):
+            ids = args[i + 1]; i += 2
+        else:
+            positional.append(args[i]); i += 1
+    
+    if positional:
+        query = " ".join(positional)
+    
+    search(query=query, author=author, category=category, ids=ids, max_results=max_results, sort=sort)