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Systematic strategies for searching scientific literature across PubMed, arXiv, Google Scholar, and AI-assisted tools. Covers PICO framework for clinical questions, three-tiered search (database-specific, AI-assisted, content extraction), PubMed field tags and MeSH, boolean query construction, and full-text extraction.
Passed 20 of 22 test cases with the skill, and 10 of 22 without it.
and 10 more in the full report
11 fixed10 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
How do I syntax-code a date filter in a PubMed query string to strictly limit results to articles published between January 1, 2021 and December 31, 2024?
| Checked | Without skill | With skill |
|---|---|---|
| Uses the PubMed publication date field tag syntax `"2021/01/01"[Date - Publication]:"2024/12/31"[Date - Publication]`. | Missed | Passed |
The instructions your model reads when the skill loads.
Scientific literature search is the foundation of evidence-based research. A well-executed search maximizes recall (finding all relevant papers) while maintaining precision (avoiding irrelevant results). This guide provides a systematic approach that combines database-specific query strategies, AI-assisted synthesis, and direct content extraction, organized into a three-tiered framework that scales from targeted lookups to comprehensive landscape reviews.
For clinical and biomedical questions, structure queries using the PICO framework:
PICO queries can be combined with publication type filters to target specific evidence levels:
"Diabetes Mellitus"[MeSH] AND "Metformin"[MeSH] AND "Cardiovascular Diseases"[MeSH] AND ("clinical trial"[Publication Type] OR "meta-analysis"[Publication Type])
Literature search is most effective when approached in tiers of increasing breadth:
Tier 1 -- Database-Specific Searches (Most Reliable)
Query established academic databases (PubMed, arXiv, Google Scholar) for peer-reviewed, indexed content. This is the most reliable tier and should always be the starting point.
Bio.Entrez): Primary database for biomedical and life science literature. Supports MeSH controlled vocabulary and advanced field tags.arxiv package): Preprint server for physics, mathematics, computer science, and quantitative biology. Results appear faster than peer-reviewed journals.scholarly package): Broadest coverage across all academic disciplines. Note: has aggressive rate limits on automated queries.Best for: finding specific papers, systematic reviews, clinical evidence, preprints.
Tier 2 -- AI-Assisted Web Search (Comprehensive)
Use the Claude API with the web_search_20250305 server-side tool to synthesize broader context, identify research trends, and surface recent developments not yet indexed in databases. Also use general web search (e.g. via the duckduckgo-search package) for protocols, tutorials, and software documentation.
test cases passed, vs 10 / 22 without
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