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google-scholar

This skill should be used when the user asks to "search Google Scholar", "find academic papers", "scholar search", "lookup papers", "find citations", "academic search", "search for papers by author", "find journal articles", "get BibTeX", "cite this paper", "download paper", or needs to search Google Scholar for academic literature via the scholar CLI tool.

DeepseekModel キュレーション済みスキル 品質 優秀 · 90 v1.0.0

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name google-scholar description This skill should be used when the user asks to "search Google Scholar", "find academic papers", "scholar search", "lookup papers", "find citations", "academic search", "search for papers by author", "find journal articles", "get BibTeX", "cite this paper", "download paper", or needs to search Google Scholar for academic literature via the scholar CLI tool. version 0.2.0 user-invocable false Google Scholar CLI (scholar) Search Google Scholar for academic papers via the scholar command-line tool. Requires: scholar on PATH ( ~/.local/bin/scholar → ~/projects/google-scholar-cli/scholar ) Check: command -v scholar || echo "MISSING: scholar CLI not installed" IRON LAW: No Hallucinated Metadata NEVER fabricate paper titles, authors, journals, years, or abstracts from memory. When the user asks about a specific paper or needs citation details: User mentions a paper ↓ Do you have the exact metadata from a scholar command in this session? ↓ YES → Use that data NO → Run scholar search/lookup --bibtex FIRST, then report Rationalization Table Excuse Reality Do Instead "I know this famous paper" Training data has wrong years, missing authors, garbled titles Run scholar lookup "title" --bibtex "I'll fill in details later" You won't — the hallucinated version sticks Get BibTeX first, present after "It's a well-known paper" Even well-known papers have co-authors you'll forget Let Google Scholar provide the metadata "The user just wants a quick answer" A wrong answer is worse than a 2-second lookup --bibtex adds seconds, not minutes Red Flags — STOP If You Catch Yourself: About to type a paper title from memory → STOP. Run scholar lookup . About to list authors without a source → STOP. Run --bibtex . Saying "published in" without verification → STOP. Check the BibTeX. Writing an abstract from memory → STOP. BibTeX includes the abstract. Authentication Before first use, authenticate by extracting cookies from an active Chrome session: # Chrome must be running with remote debugging enabled scholar auth --port 9222 Cookies are stored in ~/.google-scholar/cookies (mode 0600). Core Commands Scholar Labs Search (AI-Enhanced) Natural language search using Google Scholar Labs API: # One-shot search scholar search "what are the key papers on attention mechanisms" # JSON output for parsing scholar search "corporate disclosure and information asymmetry" --json # With BibTeX citations (includes abstracts) scholar search "attention is all you need" --bibtex # Download PDFs for results with full-text links scholar search "transformer architectures" --download # Interactive multi-turn mode (follow-up questions) scholar search --interactive Traditional Keyword Search Standard Google Scholar full-text search: # Keyword search scholar lookup "machine learning transformers" # Author search scholar lookup "author:shleifer disclosure" --json # With BibTeX scholar lookup "asset pricing" --bibtex # With PDF download scholar lookup "deep learning" --download Cite (BibTeX by Cluster ID) Fetch BibTeX directly when you already have a cluster ID from search results: # Single paper scholar cite 5Gohgn6QFikJ # Multiple papers, JSON output scholar cite 5Gohgn6QFikJ 8409835334886051453 --json Download (Single PDF) Note: --download works for open-access PDFs (arXiv, NBER, etc.) but is unreliable for papers behind library link resolvers (institutional access). For paywalled papers, return the URL and let the user download manually. scholar download "https://arxiv.org/pdf/1706.03762" --output attention.pdf Quick Reference Need Command Natural language question scholar search "question" Keyword/author search scholar lookup "keywords" BibTeX citations Add --bibtex to search/lookup BibTeX by cluster ID scholar cite <clusterId> Download PDFs Add --download to search/lookup Download single PDF scholar download "url" --output file.pdf JSON output Add --json to any command Interactive follow-ups scholar search --interactive Re-authenticate scholar auth Decision Tree: Which Command? Do you have a cluster ID already? YES → scholar cite <clusterId> NO ↓ Do you have a natural language research question? YES → scholar search "question" NO ↓ Do you need keyword-exact or author-specific results? YES → scholar lookup "author:name keyword" NO ↓ Do you want follow-up refinement? YES → scholar search --interactive When to add flags: Need citation metadata (authors, journal, year, abstract)? YES → Add --bibtex Need to download the PDF (open-access only)? YES → Add --download (unreliable for paywalled papers — return the URL instead) Need machine-readable output? YES → Add --json Verified Paper Information Workflow When presenting paper information to the user, follow this workflow: 1. Run scholar search/lookup with --bibtex 2. Parse BibTeX fields for authoritative metadata: - title, author, journal/booktitle, year, abstract 3. Present ONLY the fields returned by BibTeX 4. If BibTeX is missing a field, say "not available" — do NOT fill from memory BibTeX includes abstracts: The --bibtex flag injects the snippet as an abstract field in the BibTeX entry. Use this instead of generating abstracts. Output Format Table output (default): Columns for #, Title, Authors, Year, Cited, Journal, followed by snippets and URLs. JSON output ( --json ): Array of ScholarResult objects: { "title" : "Paper Title" , "authors" : "Author A, Author B" , "journal" : "Journal Name" , "year" : "2024" , "citations" : 150 , "snippet" : "Abstract excerpt..." , "url" : "https://..." , "pdfUrl" : "https://... or null" , "clusterId" : "12345" , "position" : 1 } BibTeX output ( --bibtex ): Standard BibTeX entries with abstract field: @article{key, title={Paper Title}, author={Author, A and Author, B}, journal={Journal Name}, year={2024}, abstract={Abstract text from Google Scholar snippet...} } Domain Knowledge Integration When searching Google Scholar, ALWAYS consult the domain knowledge file first: File: domain-knowledge.local.md (relative to this skill's base directory) This file contains the user's curated list of trusted journals, authors, and research groups. Use it to: Prioritize results from known-good journals and authors Flag unfamiliar sources - if a result is from an unknown journal, note it Suggest related searches - use known authors to refine queries Assess quality - weight results higher when they appear in trusted venues How to Use Domain Knowledge User asks: "find papers on corporate disclosure" ↓ 1. Read domain-knowledge.local.md 2. Run scholar search/lookup 3. Cross-reference results against trusted journals/authors 4. Present results with quality signals: - ★ = from trusted journal or by trusted author - Results from unknown sources shown without star Operational Rules No hallucinated metadata — NEVER cite title/author/journal/year/abstract from memory. Use --bibtex or scholar cite to get verified data. Scholar is for discovery — Use it to find new papers, not to read them Always use --json when results will be processed programmatically Use --bibtex when presenting papers — It provides verified author, journal, year, and abstract fields Cross-reference domain knowledge — Always check trusted journals/authors Auth required — If search fails with auth errors, re-run scholar auth Rate limits — Google Scholar may rate-limit; space out rapid queries
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formatフォーマット識別子(skill/v1)
skill_idスキル固有 ID
nameスキル名
versionバージョン
description説明
categoryカテゴリ(配列)
trigger_wordsトリガーワード
tagsタグ
sourceソース
source_urlソース URL(本ページ)
exported_atエクスポート日時(ダウンロード毎)
system_promptシステムプロンプト本文
model_configモデル設定:provider / model / temperature / max_tokens / top_p
examplesサンプル
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.skill 標準形式。system_prompt と model_config を収録し、任意の Agent で利用可能 ダウンロード
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