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PubMed search with keyword optimization, result parsing, and metadata extraction
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills --skill searching-scientific-literatureコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
SOC 職業分類に基づく
SKILL.md を表示中
| name | Searching Scientific Literature |
| description | PubMed search with keyword optimization, result parsing, and metadata extraction |
| when_to_use | When starting literature search. When user asks about papers, publications, studies. When need to find scientific articles. When building initial paper list for research question. |
| version | 1.0.0 |
Search PubMed for scientific literature using optimized queries. Extract metadata and prepare papers for relevance evaluation.
Core principle: Cast a wide enough net to find relevant papers, but use targeted keywords to keep results manageable.
Use this skill when:
Extract:
Boolean operators:
Example queries:
"BTK inhibitor"[Title/Abstract] AND selectivity[Title/Abstract]
("kinase inhibitor" OR "protein kinase") AND (selectivity OR "off-target")
"ibrutinib"[Title/Abstract] AND ("IC50" OR "inhibitory concentration")
Field tags:
[Title/Abstract] - search title and abstract only[Title] - title only (more precise)[Author] - specific author[Journal] - specific journal[Date] - date rangeAPI endpoint:
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?\
db=pubmed&\
term=YOUR_QUERY&\
retmax=100&\
retmode=json&\
sort=relevance
Parameters:
db=pubmed - search PubMed databaseterm= - your query (URL encode spaces and special chars)retmax=100 - max results (start with 100)retmode=json - return JSONsort=relevance - most relevant first (or pub_date for newest)Example bash:
curl "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&term=BTK+inhibitor+selectivity&retmax=100&retmode=json&sort=relevance"
Response format:
{
"esearchresult": {
"count": "156",
"retmax": "100",
"idlist": ["12345678", "87654321", ...]
}
}
API endpoint:
https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?\
db=pubmed&\
id=12345678,87654321&\
retmode=json
Extract from response:
articleids)Getting DOI from PMID:
"articleids": [
{"idtype": "pubmed", "value": "12345678"},
{"idtype": "doi", "value": "10.1234/example.2023"}
]
If DOI missing:
Create list of paper objects:
[
{
"pmid": "12345678",
"doi": "10.1234/example.2023",
"title": "Selective BTK inhibitors for autoimmune diseases",
"authors": ["Smith J", "Doe A", "Johnson B"],
"journal": "Nature Chemical Biology",
"year": "2023",
"abstract": "We developed a series of...",
"source": "pubmed_search"
}
]
Rate limits (CRITICAL - shared across all processes/subagents):
delay_seconds = (num_parallel / rate_limit) + safety_marginEmpty results:
Too many results (>500):
After search completes:
initial-search-results.jsonevaluating-paper-relevance skillpapers-reviewed.json (use DOI as key, fallback to PMID)| Task | Command |
|---|---|
| Search PubMed | curl "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&term=QUERY&retmax=100&retmode=json" |
| Get metadata | curl "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi?db=pubmed&id=PMID1,PMID2&retmode=json" |
| URL encode query | Replace spaces with +, special chars with %XX |
| Narrow results | Use AND, add field tags, more specific terms |
| Broaden results | Use OR, remove field tags, add synonyms |
Too narrow: Only 5 results → Use OR, remove constraints Too broad: 5000 results → Add AND terms, use field tags Missing abstracts: Use efetch instead of esummary for full abstract text DOI not found: Many older papers lack DOI - use PMID as fallback Rate limiting: Add 500ms delays (single agent) or longer (parallel subagents sharing rate limit)
After completing search:
skills/research/evaluating-paper-relevance