| name | pubmed |
| description | PubMed — NCBI's biomedical literature database (>35M citations). Keyword search inline, or batch-fetch full title + structured abstract + authors + DOI for a known list of PMIDs. Use for medical / biological literature lookup, citation resolution, or building an abstract corpus for downstream NLP. Honors NCBI_API_KEY env var. |
| license | Unknown |
| metadata | {"skill-author":"VenusFactory2 (download_pubmed_abstracts_by_pmids adapted from Google DeepMind)."} |
PubMed
Overview
Two complementary tools: existing query_pubmed_tool (keyword search, returns small JSON inline) + new download_pubmed_abstracts_by_pmids (batch-fetch full abstracts by PMID list, one efetch XML call, saves normalized JSON to disk).
Project Tools (VenusFactory2)
| Tool | Args | Returns | Description |
|---|
| query_pubmed | query (text), max_results (default 5, max 50), max_content_length | JSON list of paper records inline | Keyword search; small payload to agent. |
| download_pubmed_abstracts_by_pmids | pmids (list of PMID strings, max 200 per call), out_path (JSON file path), timeout (default 60s) | rich JSON envelope; saved file is {requested_pmids, articles[]} where each article has pmid, title, authors, journal, year, doi, abstract (structured abstracts join Label: body segments with newlines) | Batch-fetch full abstracts + metadata by PMID via efetch. |
When to Use Each
| Goal | Tool |
|---|
| "Find papers about X" | query_pubmed |
| "Get me the full abstracts for these 50 PMIDs" | download_pubmed_abstracts_by_pmids |
| Build a corpus for fine-tuning a biomedical NLP model | query_pubmed → collect PMIDs → batch fetch via download_pubmed_abstracts_by_pmids |
| Resolve a citation string to a PMID | (out of scope here — use the search tool with the citation text, parse hits) |
Output Schema for download_pubmed_abstracts_by_pmids
{
"requested_pmids": ["34265844", "37962427", ...],
"articles": [
{
"pmid": "34265844",
"title": "Highly accurate protein structure prediction with AlphaFold",
"authors": ["Jumper J", "Evans R", ...],
"journal": "Nature",
"year": "2021",
"doi": "10.1038/s41586-021-03819-2",
"abstract": "Proteins are essential to life..."
},
...
]
}
Structured abstracts (with BACKGROUND:/METHODS:/RESULTS:/CONCLUSIONS: sections) are joined with \n and each section is prefixed by its label.
Rate Limiting
- Without
NCBI_API_KEY: 3 req/s.
- With
NCBI_API_KEY (free; get at https://www.ncbi.nlm.nih.gov/account/settings/): 10 req/s.
download_pubmed_abstracts_by_pmids does ONE efetch for the whole batch — much friendlier than N individual fetches.- Hard cap: 200 PMIDs per call (split into chunks if you need more).
Common Mistakes
- PMID as int: the tool accepts strings; pass
"34265844", not 34265844. (Int is coerced to str internally but use string defensively.)
- >200 PMIDs in one call: returns
ValidationError. Split into chunks of ≤200.
- Missing abstract: not all PubMed records have abstracts (older / non-research / book chapters). The
abstract field will be null for those.
- Confusing PMID with PMCID: PMID is a number (e.g.
34265844); PMCID is PMC<number> (e.g. PMC8371605). This tool uses PMIDs.
References
