semantic-scholar
Search Semantic Scholar for academic papers across all disciplines with citation graph analysis. Use when: (1) finding papers across disciplines, (2) citation/reference graph traversal, (3) author search, (4) paper recommendations, (5) large-scale bibliometric analysis. NOT for: specific database access (use pubmed for biomedical, arxiv for preprints).
Best use case
semantic-scholar is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Search Semantic Scholar for academic papers across all disciplines with citation graph analysis. Use when: (1) finding papers across disciplines, (2) citation/reference graph traversal, (3) author search, (4) paper recommendations, (5) large-scale bibliometric analysis. NOT for: specific database access (use pubmed for biomedical, arxiv for preprints).
Teams using semantic-scholar should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/semantic-scholar/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How semantic-scholar Compares
| Feature / Agent | semantic-scholar | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Search Semantic Scholar for academic papers across all disciplines with citation graph analysis. Use when: (1) finding papers across disciplines, (2) citation/reference graph traversal, (3) author search, (4) paper recommendations, (5) large-scale bibliometric analysis. NOT for: specific database access (use pubmed for biomedical, arxiv for preprints).
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Semantic Scholar Search
Search 200M+ papers across all disciplines with citation graph, author profiles,
and recommendations via the Semantic Scholar API.
## Authentication
```bash
curl -s -H "x-api-key: ${S2_API_KEY}" "https://api.semanticscholar.org/graph/v1/paper/search?query=example"
```
## Paper Search
```bash
curl -s "https://api.semanticscholar.org/graph/v1/paper/search?query=machine+learning+drug+discovery&limit=5&fields=title,authors,year,abstract,citationCount,url"
```
Parameters: `query=` (required), `limit=` (max 100), `offset=`, `fields=`,
`year=` (e.g. `2020-2024`), `fieldsOfStudy=` (e.g. `Computer Science`, `Medicine`),
`openAccessPdf`, `minCitationCount=`.
**Bulk search** (up to 10M results, token-based pagination):
```bash
curl -s "https://api.semanticscholar.org/graph/v1/paper/search/bulk?query=CRISPR+gene+editing&fields=title,year,citationCount"
```
## Paper Lookup by Identifier
```bash
# DOI
curl -s "https://api.semanticscholar.org/graph/v1/paper/DOI:10.1038/s41586-021-03819-2?fields=title,abstract,authors,year,citationCount"
# arXiv ID
curl -s "https://api.semanticscholar.org/graph/v1/paper/ARXIV:2301.07041?fields=title,abstract,year"
# PubMed ID
curl -s "https://api.semanticscholar.org/graph/v1/paper/PMID:34265844?fields=title,abstract,year"
```
## Citation Graph
```bash
# Papers that cite a given paper
curl -s "https://api.semanticscholar.org/graph/v1/paper/ARXIV:2301.07041/citations?fields=title,year,citationCount&limit=20"
# Papers cited by a given paper
curl -s "https://api.semanticscholar.org/graph/v1/paper/ARXIV:2301.07041/references?fields=title,year,citationCount&limit=20"
```
## Author Search
```bash
# Search by name
curl -s "https://api.semanticscholar.org/graph/v1/author/search?query=yann+lecun&fields=name,hIndex,paperCount,citationCount"
# Author papers
curl -s "https://api.semanticscholar.org/graph/v1/author/1688681/papers?fields=title,year,citationCount&limit=20"
```
## Recommendations
```bash
# Single-paper
curl -s "https://api.semanticscholar.org/recommendations/v1/papers/forpaper/ARXIV:2301.07041?fields=title,year,citationCount&limit=10"
# Multi-paper (POST)
curl -s -X POST "https://api.semanticscholar.org/recommendations/v1/papers/" \
-H "Content-Type: application/json" \
-d '{"positivePaperIds": ["ARXIV:2301.07041", "ARXIV:2302.13971"], "negativePaperIds": []}'
```
## Available Fields
**Paper**: `paperId`, `title`, `abstract`, `year`, `venue`, `citationCount`,
`referenceCount`, `influentialCitationCount`, `isOpenAccess`, `openAccessPdf`,
`fieldsOfStudy`, `publicationTypes`, `publicationDate`, `journal`, `url`,
`externalIds`, `tldr`
**Nested**: `authors.name`, `authors.authorId`, `citations.title`, `references.title`
## Rate Limits
- Without API key: 100 requests per 5 minutes
- With API key: 1/sec sustained, 10/sec burst
- Register free at: https://www.semanticscholar.org/product/api#api-key
- HTTP 429 on rate limit; back off and retry
## Ready-to-Use Query Templates
### Find recent high-impact papers on a topic
```bash
curl -s "https://api.semanticscholar.org/graph/v1/paper/search?\
query=YOUR+TOPIC&limit=10&year=2023-2025&minCitationCount=10&\
fields=title,authors,year,citationCount,influentialCitationCount,tldr,venue,isOpenAccess,openAccessPdf,externalIds" \
| python3 -c "
import sys, json
data = json.load(sys.stdin)
print(f'Found {data[\"total\"]} papers')
for i, p in enumerate(data['data']):
authors = ', '.join(a['name'] for a in (p.get('authors') or [])[:3])
tldr = (p.get('tldr') or {}).get('text', 'N/A')[:120]
doi = (p.get('externalIds') or {}).get('DOI', 'N/A')
print(f'[{i+1}] {p[\"title\"]}')
print(f' {authors} ({p.get(\"year\")}) {p.get(\"venue\",\"\")} Cited:{p[\"citationCount\"]}')
print(f' TLDR: {tldr}')
print(f' DOI: {doi}')
print()
"
```
### Build citation graph for a paper
```bash
PAPER_ID="DOI:10.1038/s41586-021-03819-2" # or ARXIV:2301.07041 or S2 ID
# Who cites this?
curl -s "https://api.semanticscholar.org/graph/v1/paper/${PAPER_ID}/citations?\
fields=title,year,citationCount,venue&limit=20" | python3 -c "
import sys,json; data=json.load(sys.stdin)
print(f'{len(data[\"data\"])} citing papers:')
for c in sorted(data['data'], key=lambda x: x['citingPaper'].get('citationCount',0), reverse=True)[:10]:
p=c['citingPaper']
print(f' [{p.get(\"year\",\"?\")}] {p[\"title\"][:80]} (cited:{p.get(\"citationCount\",0)})')
"
```
### Find open access PDF for a paper
```bash
curl -s "https://api.semanticscholar.org/graph/v1/paper/DOI:10.xxxx/xxxxx?\
fields=title,isOpenAccess,openAccessPdf" | python3 -c "
import sys,json; p=json.load(sys.stdin)
pdf = p.get('openAccessPdf',{})
if pdf: print(f'OA PDF: {pdf[\"url\"]}')
else: print('No open access PDF available')
"
```
## Best Practices
1. Always specify `fields=` to reduce response size.
2. Use `minCitationCount` to filter low-impact results.
3. Use external IDs (DOI, ARXIV, PMID) for precise lookups.
4. Chain citation/reference lookups to build citation graphs.
5. Use `tldr` field for AI-generated paper summaries.
6. Use `influentialCitationCount` to identify high-impact papers.
7. **Prefer Semantic Scholar over CrossRef** for paper discovery searches.
8. Combine with OpenAlex for broader coverage and OA link discovery.
9. **NEVER fabricate results.** Every paper detail must come from an actual API response. If the API returns no results, report that honestly.
10. **Self-check before responding:** Did this paper title, DOI, author list, and citation count ALL come from an S2 API call in this conversation?Related Skills
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