mining-pubmed-literature
Searches and fetches PubMed and PMC via NCBI E-utilities (ESearch then EFetch/ESummary) to gather biomedical evidence and build text corpora. Use when the user wants citations for a condition or drug, abstracts to summarize, MeSH-based searches, or a corpus of literature to run NER over. Trigger keywords: PubMed, PMC, NCBI, E-utilities, ESearch, EFetch, ESummary, MeSH, PMID, literature search, abstracts, evidence. Pairs adjacent to OpenMed: fetched abstracts feed openmed.analyze_text for biomedical NER, and OpenMed-extracted diagnoses/drugs/genes become the search terms. E-utilities are public
Profile →npx skills add maziyarpanahi/openmed --skill mining-pubmed-literature --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Mining PubMed & PMC literature (NCBI E-utilities) Search **PubMed** (citations/abstracts) and **PMC** (full text) programmatically with **NCBI E-utilities** — the stable HTTP interface to Entrez. The core pattern is two steps: **ESearch** returns matching record IDs (PMIDs), then **EFetch** (or **ESummary**) downloads the records. The **Entrez History server** (`usehistory=y`) lets you chain the two without re-sending thousands of IDs. E-utilities are public. **No key is required**, but a free API key raises your limit from **3 to 10 requests/second** and is strongly recommended for batch work. ## When to use - OpenMed extracted a diagnosis, drug, or gene and you want supporting literature. - You need abstracts to summarize or to assemble a corpus for biomedical NER. - You want MeSH-anchored, reproducible searches (date ranges, article types). For ClinicalTrials.gov use `searching-clinicaltrials`; this skill is for the published literature. ## Quick start (real E-utilities calls) Base URL: `https://eutils.ncbi.nlm.nih.gov/entrez/eutils/`. JSON for ESearch/ ESummary via `retmode=json`; EFetch returns text or XML (no JSON for PubMed). ```python import requests, time BASE = "https:/
- When to use
- Quick start (real E-utilities calls)
- ESummary for structured metadata
- Workflow
- Hand-off to / from OpenMed
- Edge cases & gotchas
- Standards & references
curl "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&term=metformin&retmode=json" curl "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&id=38000000&rettype=abstract&retmode=text"
What does the mining-pubmed-literature skill do?
Searches and fetches PubMed and PMC via NCBI E-utilities (ESearch then EFetch/ESummary) to gather biomedical evidence and build text corpora. Use when the user wants citations for a condition or drug, abstracts to summarize, MeSH-based searches, or a corpus of literature to run NER over. Trigger keywords: PubMed, PMC, NCBI, E-utilities, ESearch, EFetch, ESummary, MeSH, PMID, literature search, abstracts, evidence. Pairs adjacent to OpenMed: fetched abstracts feed openmed.analyze_text for biomedical NER, and OpenMed-extracted diagnoses/drugs/genes become the search terms. E-utilities are public
How do I install it?
Run `npx skills add maziyarpanahi/openmed --skill mining-pubmed-literature --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From maziyarpanahi/openmed, a repository with 4,851 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.