Semantic Scholar Paper Search

Search topic or paper ID: $ARGUMENTS

Role & Positioning

This skill is the published venue counterpart to

/arxiv

/arxiv

/semantic-scholar

Do NOT duplicate arXiv's job. If results contain an

externalIds.ArXiv

Constants

• MAX_RESULTS = 10 — Default number of search results.
• FETCH_SCRIPT —

  tools/semantic_scholar_fetch.py

  relative to the project root. Fall back to inline Python if not found.
• DEFAULT_FILTERS — For general research queries, apply these by default to reduce noise:

  • --fields-of-study "Computer Science,Engineering"

  • --publication-types JournalArticle,Conference

Overrides (append to arguments):

• /semantic-scholar "topic" - max: 20

  — return up to 20 results

• /semantic-scholar "topic" - type: journal

  — only journal articles

• /semantic-scholar "topic" - type: conference

  — only conference papers

• /semantic-scholar "topic" - min-citations: 50

  — only highly-cited papers

• /semantic-scholar "topic" - year: 2022-

  — papers from 2022 onward

• /semantic-scholar "topic" - fields: all

  — remove default field-of-study filter

• /semantic-scholar "topic" - sort: citations

  — bulk search sorted by citation count

• /semantic-scholar "DOI:10.1109/..."

  — fetch a single paper by DOI

Workflow

Step 1: Parse Arguments

Parse

$ARGUMENTS

• Query or ID: main search term, or a paper identifier:
  • DOI:

    10.1109/TWC.2024.1234567

  • Semantic Scholar ID:

    f9314fd99be5f2b1b3efcfab87197d578160d553

  • ArXiv:

    ARXIV:2006.10685

  • Corpus:

    CorpusId:219792180

• - max: N

  : override MAX_RESULTS

• - type: journal|conference|review|all

  : map to

  --publication-types

• - min-citations: N

  : map to

  --min-citations

• - year: RANGE

  : map to

  --year

  (e.g.

  2022-

  ,

  2020-2024

  )

• - fields: FIELDS

  : override

  --fields-of-study

  (use

  all

  to remove filter)

• - sort: citations|date

  : use

  search-bulk

  with

  --sort citationCount:desc

  or

  publicationDate:desc

If the argument matches a DOI pattern (

10.XXXX/...

ARXIV:...

CorpusId:...

Step 2: Search Papers

Locate the fetch script:

SCRIPT=$(find tools/ -name "semantic_scholar_fetch.py" 2>/dev/null | head -1)
[ -z "$SCRIPT" ] && SCRIPT=$(find ~/.claude/skills/semantic-scholar/ -name "semantic_scholar_fetch.py" 2>/dev/null | head -1)

Standard search (default — relevance-ranked):

python3 "$SCRIPT" search "QUERY" --max MAX_RESULTS \
  --fields-of-study "Computer Science,Engineering" \
  --publication-types JournalArticle,Conference

Bulk search (when

- sort:

python3 "$SCRIPT" search-bulk "QUERY" --max MAX_RESULTS \
  --sort citationCount:desc \
  --fields-of-study "Computer Science" \
  --year "2020-"

If

semantic_scholar_fetch.py

urllib

https://api.semanticscholar.org/graph/v1/paper/search

Recommended filter combos (from testing):

--publication-types JournalArticle --min-citations 10

--fields-of-study "Computer Science,Engineering" --year "2022-"

search-bulk --sort citationCount:desc --fields-of-study "Computer Science"

--publication-types Conference

Note:

--venue

requires exact venue names (e.g. "IEEE Transactions on Signal Processing"), not partial matches like "IEEE". Avoid using

--venue

in automated flows — prefer

--publication-types

+

--fields-of-study

.

Step 3: Fetch Details for a Specific Paper

When a single paper ID is requested:

python3 "$SCRIPT" paper "PAPER_ID"

Where PAPER_ID can be:

• DOI:

  10.1109/TSP.2021.3071210

• ArXiv:

  ARXIV:2006.10685

• CorpusId:

  CorpusId:219792180

• S2 ID:

  f9314fd99be5f2b1b3efcfab87197d578160d553

Step 4: De-duplicate Against arXiv

For each result, check

externalIds.ArXiv

• If present → paper is also on arXiv. Note this in output but do NOT re-fetch via

  /arxiv

  .
• If absent → paper is venue-only (e.g. IEEE without preprint). This is the unique value of this skill.

Step 5: Present Results

Present results as a table:

| # | Title | Venue | Year | Citations | Authors | Type |
|---|-------|-------|------|-----------|---------|------|
| 1 | Deep Learning Enabled... | IEEE Trans. Signal Process. | 2021 | 1364 | Xie et al. | Journal |

For each paper, also show:

• DOI link:

  https://doi.org/DOI

  (for IEEE/ACM papers, this is the canonical link)
• Open Access PDF: if

  openAccessPdf.url

  is non-empty, show it
• TLDR: if available, show the one-line summary
• Also on arXiv: if

  externalIds.ArXiv

  exists, note the arXiv ID

Step 6: Detailed Summary

For each paper (or top 5 if many results):

## [Title]

- **Venue**: [venue name] ([publicationVenue.type]: journal/conference)
- **Year**: [year] | **Citations**: [citationCount]
- **Authors**: [full author list]
- **DOI**: [doi link]
- **Fields**: [fieldsOfStudy]
- **TLDR**: [tldr.text if available]
- **Abstract**: [abstract]
- **Open Access**: [openAccessPdf.url or "Not available"]
- **Also on arXiv**: [ArXiv ID if exists, else "No"]

Step 7: Final Output

Summarize what was done:

• Found N published papers for "query"

• Filters applied: [publication types, fields, year range, etc.]

• N papers are venue-only (not on arXiv)

Suggest follow-up skills:

/arxiv "topic"           - search arXiv preprints (complements this search)
/research-lit "topic"    - multi-source review: Zotero + local PDFs + arXiv + S2
/novelty-check "idea"    - verify novelty against literature

Key Rules

• Default to filtered search: Always apply

  --fields-of-study

  and

  --publication-types

  unless user says

  - fields: all

  . Without filters, S2 returns cross-discipline noise (linguistics, psychology, etc.).
• Citation count is gold: S2's citation data is its main advantage over arXiv. Always show

  citationCount

  prominently and use it to rank/prioritize results.
• Venue metadata matters: Show

  venue

  and

  publicationVenue.type

  (journal vs conference) — this helps users assess paper quality.
• DOI is the canonical ID for published papers: Always show DOI links for IEEE/ACM/Springer papers.
• Rate limiting: S2 API without key is heavily rate-limited (~1 req/s, strict cooldown). If HTTP 429 occurs, wait and retry. Recommend users set

  SEMANTIC_SCHOLAR_API_KEY

  env var for higher limits (free at https://www.semanticscholar.org/product/api#api-key-form).
• TLDR may be null: Some publishers (notably IEEE) elide the TLDR field. Fall back to showing the first sentence of the abstract.
• openAccessPdf may be empty: Many IEEE papers are closed access. Always provide the DOI link as fallback.
• If the S2 API is unreachable, suggest using

  /arxiv

  or

  /research-lit "topic" - sources: web

  as fallback.