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帮助用户检索 PubMed 生物医学文献、MeSH 主题词与 PMID 引文信息。
复制安装指令，让 AI 自动完成配置 · 推荐新手
请帮我安装 askskill 上的 "pubmed-database" 技能： 1. 下载 https://raw.githubusercontent.com/affaan-m/ECC/main/skills/scientific-db-pubmed-database/SKILL.md 2. 保存为 ~/.claude/skills/scientific-db-pubmed-database/SKILL.md 3. 装好后重载技能，告诉我可以用了
请在 PubMed 中检索过去 3 年关于阿尔茨海默病早期诊断生物标志物的英文论文，按相关性排序，返回标题、PMID、发表年份和摘要摘要。
返回相关论文列表，包含基础引文信息与内容摘要，便于快速筛选。
帮我查找与 2 型糖尿病和胰岛素抵抗相关的 MeSH 主题词，并说明每个词的适用范围，方便我构建检索式。
输出相关 MeSH 词、定义或范围说明，以及可用于检索的组合建议。
根据以下 PMID 列表获取标准引文信息：31234567、33456789、35678901。请整理为 APA 格式，并补充期刊名、作者和 DOI。
返回规范化引文结果，可直接用于论文写作或文献管理工具导入。
Use this skill when a task needs biomedical literature from PubMed rather than general web search.
Start with the research question, split it into concepts, then combine concepts with Boolean operators.
concept_1 AND concept_2 AND filter
synonym_a OR synonym_b
NOT exclusion_term
Useful PubMed field tags:
[ti]: title[ab]: abstract[tiab]: title or abstract[au]: author[ta]: journal title abbreviation[mh]: MeSH term[majr]: major MeSH topic[pt]: publication type[dp]: date of publication[la]: languageExamples:
diabetes mellitus[mh] AND treatment[tiab] AND systematic review[pt] AND 2023:2026[dp]
(metformin[nm] OR insulin[nm]) AND diabetes mellitus, type 2[mh] AND randomized controlled trial[pt]
smith ja[au] AND cancer[tiab] AND 2026[dp] AND english[la]
Prefer MeSH when the concept has a stable controlled-vocabulary term. Combine MeSH with title/abstract terms when the topic is new or terminology varies.
Correct subheading syntax puts the subheading before the field tag:
diabetes mellitus, type 2/drug therapy[mh]
cardiovascular diseases/prevention & control[mh]
Use [majr] only when the topic must be central to the paper. It can improve
precision but may miss relevant work.
Publication types:
clinical trial[pt]meta-analysis[pt]randomized controlled trial[pt]review[pt]systematic review[pt]guideline[pt]Date filters:
2026[dp]
2020:2026[dp]
2026/03/15[dp]
Availability filters:
free full text[sb]
hasabstract[text]
NCBI E-utilities supports repeatable API workflows:
esearch.fcgi: search and return PMIDs.esummary.fcgi: return lightweight article metadata.efetch.fcgi: fetch abstracts or full records in XML, MEDLINE, or text.elink.fcgi: find related articles and linked resources.Use an email and API key for production scripts. Store API keys in environment variables, never in committed files or command history.
import os
import time
import requests
BASE = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils"
def esearch(query: str, retmax: int = 20) -> list[str]:
params = {
"db": "pubmed",
"term": query,
"retmode": "json",
"retmax": retmax,
"tool": "ecc-pubmed-search",
"email": os.environ.get("NCBI_EMAIL", ""),
}
api_key = os.environ.get("NCBI_API_KEY")
if api_key:
params["api_key"] = api_key
response = requests.get(f"{BASE}/esearch.fcgi", params=params, timeout=30)
response.raise_for_status()
time.sleep(0.35)
return response.json()["esearchresult"]["idlist"]
pmids = esearch("hypertension[mh] AND randomized controlled trial[pt] AND 2024:2026[dp]")
print(pmids)
For batches, prefer NCBI history server parameters (usehistory=y,
WebEnv, query_key) instead of passing very long PMID lists through URLs.
For each search pass, record:
Example:
| Database | Date searched | Query | Filters | Results |
| --- | --- | --- | --- | ---: |
| PubMed | 2026-05-11 | `sickle cell disease[mh] AND CRISPR[tiab]` | 2020:2026[dp], English | 42 |
…
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为 AI 代理提供结构化 PubMed 文献检索、缓存与开放全文下载能力。