ai4scholar-paper-search

name	ai4scholar-paper-search
description	Use AI4Scholar to search real scholarly papers across Semantic Scholar, PubMed, Google Scholar, arXiv, bioRxiv, and medRxiv. Trigger for AI4Scholar paper search, latest literature, top journal literature discovery, cross-database search, paper search prompts, or when the user needs traceable real references rather than invented citations.

AI4Scholar Paper Search

Use this skill to search real scholarly literature through AI4Scholar MCP or the OpenClaw AI4Scholar plugin.

Source guide: https://lifu-coze.feishu.cn/wiki/WOaewK33Ei2g1nkt44kcRXiBnze
AI4Scholar MCP endpoint: https://mcp.ai4scholar.net/sse

Non-Negotiable Rules

• Never fabricate references.
• Never expose an API key. Use ${AI4SCHOLAR_API_KEY} or "your AI4Scholar API key".
• Prefer verified identifiers: DOI, PMID, arXiv ID, Semantic Scholar ID, publisher URL.
• Mark unverifiable or weakly matched results as needing manual verification.
• For management, psychology, neuroscience, BCI, HCI, and text-mining topics, search both classic and recent papers when possible.

Tools From The Source Guide

Use the exact schemas exposed by the MCP server or plugin. Common search tools described by the source guide include:

Tool	Source	Best use
search_semantic	Semantic Scholar	Broad semantic literature search with year filters
search_pubmed	PubMed	Biomedical, psychology-adjacent, neuroscience, clinical, health topics
search_google_scholar	Google Scholar proxy	Broad cross-disciplinary discovery
search_arxiv	arXiv	AI, ML, CS, BCI algorithms, HCI preprints
search_biorxiv	bioRxiv	Biology and neuroscience preprints
search_medrxiv	medRxiv	Medical and clinical preprints
search_semantic_snippets	Semantic Scholar	Search text snippets inside paper full text
search_semantic_bulk	Semantic Scholar	Large search, up to 1000 results if supported
search_semantic_paper_match	Semantic Scholar	Exact title matching

Search Workflow

1. Convert the user question into 2-4 precise English queries. Add Chinese queries only when Chinese literature is relevant.
2. Choose databases:
   • Management, psychology, HCI, IS: Semantic Scholar + Google Scholar.
   • Neuroscience, EEG, ERP, BCI: PubMed + Semantic Scholar + arXiv when algorithms are involved.
   • AI/ML/text mining: arXiv + Semantic Scholar + Google Scholar.
3. Run at least two sources when available.
4. Deduplicate by DOI, title, year, and first author.
5. Prioritize:
   • recent five-year papers,
   • top journals or major conferences,
   • highly cited classics,
   • papers that match the user's method and variables.
6. Output a literature matrix before writing narrative synthesis.

Screening Criteria

Score each candidate paper from 0-2 on:

Criterion	0	1	2
Topic fit	unrelated	adjacent	directly relevant
Method fit	wrong method	partially similar	same or transferable method
Evidence quality	unclear	usable	strong design/data
Venue quality	unknown	field-normal	top or authoritative
Citation traceability	no identifier	partial metadata	DOI/PMID/arXiv/publisher URL

Keep papers scoring at least 7/10 unless the user requests broad exploration.

Output Template

Research question:
AI4Scholar mode: MCP / OpenClaw plugin / unknown
Databases searched:
Query strings:
Filters:

Top papers:
| # | Title | Authors | Year | Venue | DOI/ID | Source | Why it matters | Verification |

Excluded or weak papers:
| Title | Reason |

Next search move:

Beginner Prompt

Use AI4Scholar to search real English-language papers on "[topic]".
Prioritize the most recent five years, while keeping necessary classic papers.
Use at least Semantic Scholar plus one of PubMed, Google Scholar, or arXiv.
Return title, authors, year, venue, DOI/PMID/arXiv ID, abstract, source, and manual-verification status.

Quality Checks

• If results are empty, broaden the query and try another database.
• If the same paper appears across sources, merge the metadata instead of duplicating it.
• If a result has no DOI or stable identifier, do not cite it as verified.
• If the user asks for "top journal" evidence, explain the venue screen used.