Semantic Scholar Search

Search Semantic Scholar for papers, fetch structured metadata by paper ID or DOI, profile authors, and traverse citation graphs. Uses the official Semantic Scholar API — no scraping, structured results, free to use.

When to Use

• Discovering papers on a topic before running triage-paper
• Resolving an arxiv ID or DOI to full metadata during triage-paper step 1
• Fetching papers that cite or are cited by a known paper
• Profiling an author to find their key publications
• Preferred over google-scholar-search whenever both are available

When Not to Use

• The semantic-scholar MCP server is configured — optionally prefer it over this script; the MCP returns the same data with less setup
• The paper is in a biomedical domain not covered by Semantic Scholar — consider PubMed instead
• You need Google Scholar–exclusive sources (patents, grey literature) — use google-scholar-search

Mindset

This is a structured API, not a search engine — treat it accordingly.

1. IDs over titles: a gotcha is using a paper title as the --paper-id flag. The paper subcommand requires a Semantic Scholar paper ID, arxiv ID (prefix arXiv:), or DOI. Titles go to search.
2. Author IDs, not names: the author subcommand requires a Semantic Scholar author ID. A common pitfall is passing a name and getting "not found". Use search first to locate the author ID.
3. Rate limits apply without a key: 100 requests per 5 minutes without an API key. NEVER issue search loops that exhaust the quota; optionally set SEMANTIC_SCHOLAR_API_KEY to increase limits.

Workflow

1. Choose the right subcommand

2. Set up the environment (first run only)

See setup-and-troubleshooting.md.

3. Run the subcommand

# Keyword discovery
./scripts/semantic-scholar-search.py search \
  --query "retrieval-augmented generation" --limit 10

# Full paper metadata — Semantic Scholar ID, arxiv ID, or DOI
./scripts/semantic-scholar-search.py paper --paper-id "arXiv:2005.11401"
./scripts/semantic-scholar-search.py paper --paper-id "10.18653/v1/2020.acl-main.740"

# Author profile — requires Semantic Scholar author ID
./scripts/semantic-scholar-search.py author --author-id "1741101"

# Citations and references for a known paper
./scripts/semantic-scholar-search.py citations --paper-id "arXiv:2005.11401" --type citations
./scripts/semantic-scholar-search.py citations --paper-id "arXiv:2005.11401" --type references

# Export any result to JSON
./scripts/semantic-scholar-search.py search \
  --query "chain-of-thought reasoning" --limit 10 --format json \
  --output /tmp/candidates.json

4. Find a Semantic Scholar author ID (if needed)

# Step 1: search for the author's papers to locate their ID
./scripts/semantic-scholar-search.py search --query "<author name> <topic>" --limit 5 --format json \
  | python3 -c "import json,sys; [print(a['authorId'], a['name']) for p in json.load(sys.stdin) for a in p.get('authors',[])]"

5. Present candidates and hand off

Show results to the user. NEVER triage automatically. For each promising paper offer:

Found N results. Would you like to triage any of these with triage-paper?

For known papers, pass the arxiv ID or DOI directly to triage-paper step 1.

Anti-Patterns

NEVER pass a paper title to the paper subcommand

WHY: The paper subcommand resolves by ID only. Passing a title returns "not found" or a wrong paper.

BAD --paper-id "Attention Is All You Need" → GOOD --paper-id "arXiv:1706.03762" or the Semantic Scholar paper ID.

NEVER pass an author name to the author subcommand

WHY: The author subcommand requires a Semantic Scholar author ID (numeric string). Names are not accepted.

BAD --author-id "Yoshua Bengio" → GOOD Locate the numeric author ID via search first, then use --author-id "1794492".

NEVER loop subcommands to exhaustion

WHY: Without an API key, the rate limit is 100 requests per 5 minutes. A tight loop will trigger a 429 and block further queries.

BAD Fetch citations recursively in a loop without rate limiting. → GOOD Batch fetches with time.sleep(1) or set SEMANTIC_SCHOLAR_API_KEY for higher quota.

NEVER treat search ranking as completeness

WHY: Semantic Scholar search ranks by relevance, not publication date or citation count. The top 10 results are not "the 10 most important papers on X".

BAD Claim "here are the key papers on X" from a top-10 search. → GOOD Qualify results as "top results by Semantic Scholar relevance ranking."

NEVER auto-triage search results

WHY: Discovery and triage are separate quality gates. Auto-triaging bypasses user review.

BAD Run triage-paper on every result. → GOOD Present the candidate list; confirm with the user which papers to triage.

NEVER use DOI and Semantic Scholar ID interchangeably without the correct prefix

WHY: The API distinguishes ID types. An unprefixed DOI is treated as a Semantic Scholar paper ID and will return "not found".

BAD --paper-id "10.18653/v1/2020.acl-main.740" when the script expects an S2 ID. → GOOD Confirm the ID type; arxiv IDs need arXiv: prefix; DOIs are accepted as-is in most contexts but verify against the script's --help.

References

• Setup & troubleshooting: setup-and-troubleshooting.md
• Script source: semantic-scholar-search.py
• Dependencies: requirements.txt
• Upstream: JackKuo666/semanticScholar-search-skill
• API key: semanticscholar.org/product/api
• Preferred MCP alternative: see triage-paper for semantic-scholar MCP config