---
name: literature-search-a49eec3ab666
description: Systematic literature review methodology including search strategy, screening, and synthesis. Use when conducting literature reviews or writing background sections.
metadata:
  category: experiment
  trigger-keywords: "literature,review,systematic,PRISMA,search,database,PubMed,arXiv,citation"
  applicable-stages: "3,4,5,6"
  priority: "2"
  version: "1.0"
  author: researchclaw
  references: "adapted from K-Dense-AI/claude-scientific-skills"
---

## Literature Search Best Practice

### Search Strategy Design
1. Define research question using PICO framework (Population, Intervention, Comparison, Outcome)
2. Identify 2-4 core concepts from the research question
3. List synonyms, abbreviations, and related terms for each concept
4. Combine terms with Boolean operators: AND (between concepts), OR (within synonyms)
5. Select at least 3 complementary databases relevant to the domain:
   - Biomedical: PubMed, Scopus, Web of Science
   - Computer science: arXiv, Semantic Scholar, DBLP, ACL Anthology
   - Interdisciplinary: Google Scholar, OpenAlex
6. Document exact search strings for reproducibility

### Inclusion and Exclusion Criteria
1. Define date range (e.g., last 5-10 years for rapidly evolving fields)
2. Specify language restrictions (typically English)
3. Specify publication types (peer-reviewed, preprints, conference papers)
4. Define study design requirements (RCTs, observational, computational)
5. Set domain-specific filters (species, methodology, sample size)
6. Document all criteria BEFORE screening begins

### PRISMA Methodology
1. Record total hits from each database before deduplication
2. Remove duplicates and record count
3. Screen titles and abstracts against inclusion criteria (record excluded count)
4. Full-text review of remaining papers (record excluded with reasons)
5. Report final included studies with PRISMA flow diagram
6. For scoping reviews, use PRISMA-ScR extension

### Screening and Quality Assessment
1. Use two-pass screening: title/abstract first, then full text
2. Apply quality assessment tools appropriate to study type:
   - RCTs: Cochrane Risk of Bias tool
   - Observational: Newcastle-Ottawa Scale
   - ML papers: check reproducibility, dataset validity, statistical rigor
3. Extract data systematically using a predefined extraction form

### Synthesis Approaches
1. **Narrative synthesis**: Organize findings thematically, identify patterns and contradictions
2. **Meta-analysis**: Pool quantitative results when studies are sufficiently homogeneous
3. **Gap analysis**: Explicitly identify what is NOT covered in the literature
4. Summarize key findings per theme with supporting citation counts
5. Highlight conflicting results and possible explanations
6. End with clear statement of research gaps that motivate your study


---
Source attribution: aiming-lab
Original project: https://github.com/aiming-lab/AutoResearchClaw
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Dave AI.

## Upstream license notice

MIT License

Copyright (c) 2026 Gabriel Moreira

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Dave AI resource metadata

Creator / publisher: aiming-lab
Original project: https://github.com/aiming-lab/AutoResearchClaw
Attribution basis: Upstream repository explicitly recorded in package mirror path

Fields of work: Education & Research, Healthcare & Life Sciences
Roles: Academic Writer, Clinical Research, Researcher
Specialties: Specialty not specified
Tools: Pubmed, Arxiv, Google Scholar
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 9e1d1612ac68ae727202782b3a61861b5d6879bb4faba0b3f0770179a43d1d16