skills/43-wentorai-research-plugins/skills/literature/search/deep-literature-search/SKILL.md
Multi-source exhaustive literature search across academic databases
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research deep-literature-searchInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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A deep literature search goes beyond a quick Google Scholar query. It is a methodical, multi-source search process designed to identify all relevant publications on a topic with minimal omissions. This level of thoroughness is required for systematic reviews, meta-analyses, grant applications, and dissertation literature reviews where comprehensiveness is not optional—it is a methodological requirement.
This skill provides a structured framework for planning, executing, and documenting exhaustive literature searches across multiple academic databases. It covers query formulation using controlled vocabularies, database selection strategy, deduplication, screening workflows, and PRISMA-compliant documentation of the search process.
The framework is database-agnostic and can be applied across disciplines, from biomedical sciences (PubMed, Cochrane) to social sciences (PsycINFO, ERIC), engineering (IEEE Xplore, Compendex), and multidisciplinary databases (Web of Science, Scopus, OpenAlex).
Use the PICO/PEO/SPIDER framework appropriate to your field:
Example: "What is the effect of mindfulness-based interventions (I) on academic stress (O) in graduate students (P) compared to no intervention (C)?"
Break your research question into 2-4 key concepts. For each concept, list all synonyms, related terms, abbreviations, and controlled vocabulary terms:
| Concept | Synonyms and Related Terms | |---------|---------------------------| | Mindfulness | mindfulness-based stress reduction, MBSR, meditation, mindful awareness | | Academic stress | study stress, exam anxiety, academic burnout, student distress | | Graduate students | postgraduate, doctoral students, PhD candidates, master's students |
Combine concepts using Boolean logic:
("mindfulness" OR "MBSR" OR "mindfulness-based stress reduction" OR "meditation")
AND
("academic stress" OR "study stress" OR "exam anxiety" OR "academic burnout")
AND
("graduate student*" OR "postgraduate*" OR "doctoral student*" OR "PhD candidate*")
Key syntax rules:
OR within concept groups (broadens)AND between concept groups (narrows)* for truncation (e.g., student* matches students, student's)"" for exact phrasesNOT sparingly and document its useEach database has its own syntax and controlled vocabulary. You must translate your master search string for each target:
[MeSH] tagsTITLE-ABS-KEY() field codesTS= (Topic) and TI= (Title) field tags| Discipline | Primary Databases | Supplementary | |-----------|-------------------|---------------| | Biomedical | PubMed, Cochrane, Embase | CINAHL, PsycINFO | | Computer Science | IEEE Xplore, ACM DL, DBLP | Scopus, arXiv | | Social Sciences | PsycINFO, ERIC, Sociological Abstracts | Web of Science | | Engineering | Compendex, IEEE Xplore | Scopus, Web of Science | | Multidisciplinary | Web of Science, Scopus, OpenAlex | Google Scholar (supplementary) |
For each database:
A truly exhaustive search also covers non-indexed sources:
After collecting results from multiple databases, expect 20-40% overlap. Use reference management software to deduplicate:
Apply a two-stage screening process:
Use screening tools like Rayyan, Covidence, or ASReview to manage this process, especially for large result sets (500+ records).
Document your entire search process using the PRISMA 2020 flow diagram:
Records identified (N = ?)
├── Database 1 (n = ?)
├── Database 2 (n = ?)
└── Other sources (n = ?)
Duplicates removed (n = ?)
Records screened (n = ?)
Records excluded (n = ?)
Full-text assessed (n = ?)
Full-text excluded with reasons (n = ?)
Studies included (n = ?)
Save your complete search strategies (exact query strings, dates, result counts per database) as supplementary material for your publication. This transparency is essential for reproducibility and is increasingly required by journals.
tools
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文(用于「文献综述工具选型」与「一键安装/运行」)。
development
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
documentation
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is chosen in aer-identification and before any outcome data are seen.
tools
Guide economists to authoritative data sources with explicit, confirmed data specifications before retrieval; interfaces with Playwright MCP to navigate portals and extract real data, not articles about data.