searchapi-scholar-search（searchapi 学者搜索）

SearchAPI Scholar Search

Use this skill for paper-first retrieval. Prefer scholar-search.mjs when the user needs academic literature, candidate references, DOI clues, citation signals, or source verification for scholarly work.

This skill is especially good for:

• discovering English-language papers from a topic or question
• finding classic / highly cited papers quickly
• building an initial literature pool for a review, thesis, proposal, or grant application
• checking whether a paper title, source, year, or DOI is plausible
• finding official landing pages, publisher pages, repositories, and supporting evidence on the web

What this skill can do

1) Scholar-based paper retrieval

Run:

node {baseDir}/scripts/scholar-search.mjs "query"
node {baseDir}/scripts/scholar-search.mjs "query" -n 10 --year-from 2020 --year-to 2026
node {baseDir}/scripts/scholar-search.mjs "query" --mode review
node {baseDir}/scripts/scholar-search.mjs "query" --mode verify
node {baseDir}/scripts/scholar-search.mjs "query" --json

Returns, when available:

• paper title
• authors
• publication summary / venue clues
• year
• best verification link
• cited-by count
• snippet
• DOI / DOI URL when detected or enriched
• likely paper type (review, systematic-review, primary-study)
• search refinement suggestions
• verification hints for downstream checking

Modes:

• shortlist — default; gives a practical reading shortlist
• review — emphasizes likely review/survey-style papers for literature review workflows using heuristic title/snippet detection
• verify — emphasizes title/DOI/source verification for a likely candidate paper or claim

Use this first for:

• literature discovery
• related work exploration
• title verification
• DOI/source checking
• identifying representative papers for a topic
• getting better next-step search suggestions

2) Evidence-oriented web search

Run:

node {baseDir}/scripts/web-search.mjs "query"
node {baseDir}/scripts/web-search.mjs "query" --json

Use this after Scholar search to find:

• publisher landing pages
• DOI pages
• institutional repositories
• lab/project pages
• author homepages
• non-paper evidence related to a research topic

Recommended workflow

A. Build a candidate paper pool

Start with Scholar search using 1-3 focused queries. Example:

node {baseDir}/scripts/scholar-search.mjs "large language models higher education" -n 8 --year-from 2021 --mode shortlist

Then refine queries with:

• synonyms
• narrower task terms
• domain words
• method names
• population or setting constraints
• review / systematic review when you need overview papers first

B. Verify promising items

For strong candidates, use Scholar verify mode or web search on:

• exact paper title
• "paper title" DOI
• "paper title" publisher

This often surfaces the official landing page or repository page.

C. Normalize outputs for downstream use

After retrieval:

• deduplicate by title / DOI
• keep official or publisher links when possible
• retain cited-by counts only as rough influence signals, not quality guarantees
• convert the final shortlist into the citation format the user needs

Good query patterns

Use patterns like:

• "topic keyword" method
• "topic keyword" review
• "topic keyword" systematic review
• "topic keyword" site:doi.org via web search when verifying DOI presence
• exact title queries in quotes for verification

Examples:

node {baseDir}/scripts/scholar-search.mjs "intrusion detection deep learning review" -n 10 --year-from 2020 --mode review
node {baseDir}/scripts/scholar-search.mjs "large language models classroom teaching" -n 10 --year-from 2023 --mode shortlist
node {baseDir}/scripts/scholar-search.mjs '"Attention Is All You Need"' --mode verify
node {baseDir}/scripts/web-search.mjs '"Attention Is All You Need" DOI'

Environment variables

The scripts read the first available key from:

• SERPAPI_API_KEY
• SEARCHAPI_API_KEY

No custom base URL override is exposed in this public edition. The skill uses the default SerpApi endpoint for consistency and auditability.

Notes

• Prefer Scholar search for literature retrieval; use web search for source verification.
• Keep search batches small to avoid rate limits.
• DOI enrichment may query the public Crossref API when a DOI is not obvious in the search result.
• This skill is best used as the front end of a literature workflow: retrieve → verify → deduplicate → format citations.
• Review/survey detection is heuristic, so verify important claims on the destination page.
• For publication or academic writing tasks, do not treat search output as final truth without checking the destination page.