Semantic scholar search
Skill pantheon-org/tekhne/skills/documentation/research/semantic-scholar-search
Search Semantic Scholar for academic papers, fetch paper details by ID or DOI, retrieve author profiles, and analyse citation graphs. Preferred over google-scholar-search — uses the official API with no scraping. Triggers: search papers, find papers, semantic scholar, paper details, paper by DOI, paper by ID, author profile, citation analysis, references, literature search, paper discovery.From its SKILL.md
npx -y skills add pantheon-org/tekhne --skill semantic-scholar-searchAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 9 stars9 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
6.7 KB, ~1.6k tokens by cl100k_base, as published. Nobody here has run it
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-paperstep 1 - Fetching papers that cite or are cited by a known paper
- Profiling an author to find their key publications
- Preferred over
google-scholar-searchwhenever both are available
When Not to Use
- The
semantic-scholarMCP 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.
- IDs over titles: a gotcha is using a paper title as the
--paper-idflag. Thepapersubcommand requires a Semantic Scholar paper ID, arxiv ID (prefixarXiv:), or DOI. Titles go tosearch. - Author IDs, not names: the
authorsubcommand requires a Semantic Scholar author ID. A common pitfall is passing a name and getting "not found". Usesearchfirst to locate the author ID. - 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_KEYto increase limits.
Workflow
1. Choose the right subcommand
| Goal | Subcommand | Key flag |
|---|---|---|
| Keyword discovery | search | --query |
| Full metadata for a known paper | paper | --paper-id (SS ID, arXiv:NNNN, or DOI) |
| Author publications and h-index | author | --author-id (Semantic Scholar ID) |
| Papers citing or cited by a paper | citations | --paper-id + --type |
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-paperforsemantic-scholarMCP config
What ships with it: 8 files
22.8 KB alongside SKILL.md, 1 of them executable
evals/
- instructions.json646 B
- scenario-01.md2.1 KB
- scenario-02.md2.3 KB
- scenario-03.md2.0 KB
- summary.json69 B
references/
scripts/
- semantic-scholar-search.pyruns13.9 KB
- requirements.txt41 B