Skill: huangnong598/searchapi-scholar-search (version 1.1.0)

--- name: searchapi-scholar-search description: Academic paper discovery and evidence-oriented web search using a SerpApi/SearchAPI-compatible key. Use when the user asks for Google Scholar retrieval, paper/title/DOI/source verification, related-work discovery, foreign-language literature collection, or structured research leads for reviews, proposals, theses, and faculty/student research tasks; especially when emphasizing paper search over general web search. metadata: {"openclaw":{"requires":{"bins":["node"],"env":["SERPAPI_API_KEY","SEARCHAPI_API_KEY"]}},"clawdbot":{"emoji":"📚","requires":{"bins":["node"],"env":["SERPAPI_API_KEY","SEARCHAPI_API_KEY"]},"primaryEnv":"SERPAPI_API_KEY"}} --- # 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: ```bash 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: ```bash 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: ```bash 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: ```bash 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.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)