skills/literature/search/plos-open-access-api/SKILL.md
Search PLOS open access journals with full-text Solr-powered API
npx skillsauth add wentorai/research-plugins plos-open-access-apiInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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PLOS (Public Library of Science) publishes 7 peer-reviewed open access journals covering biology, medicine, genetics, and more. The Search API provides Solr-powered full-text search across all PLOS content — 350K+ articles, all freely available under CC-BY licenses. No authentication required. Particularly valuable for biomedical and life sciences systematic reviews.
https://api.plos.org/search
# Basic keyword search
curl "https://api.plos.org/search?q=CRISPR+gene+editing&rows=20&wt=json"
# Search in specific fields
curl "https://api.plos.org/search?q=title:\"machine learning\"+AND+abstract:biomarker&wt=json"
# Filter by journal
curl "https://api.plos.org/search?q=microbiome&fq=journal:\"PLOS ONE\"&wt=json"
# Filter by date range
curl "https://api.plos.org/search?q=COVID-19+vaccine&\
fq=publication_date:[2024-01-01T00:00:00Z TO 2026-12-31T23:59:59Z]&wt=json"
# Filter by article type
curl "https://api.plos.org/search?q=climate+change&fq=article_type:\"Research Article\"&wt=json"
# Return specific fields only
curl "https://api.plos.org/search?q=deep+learning&fl=id,title,author,publication_date,score&wt=json"
| Field | Description | Example |
|-------|-------------|---------|
| title | Article title | title:"attention mechanism" |
| abstract | Abstract text | abstract:neural+network |
| body | Full text body | body:transformer |
| author | Author name | author:"Vaswani" |
| subject | Subject area | subject:"Neuroscience" |
| journal | Journal name | journal:"PLOS Medicine" |
| Parameter | Description | Default |
|-----------|-------------|---------|
| q | Solr query (supports AND/OR/NOT) | Required |
| fq | Filter query (narrows without affecting score) | None |
| fl | Fields to return (comma-separated) | All |
| rows | Results per page (max 999) | 10 |
| start | Pagination offset | 0 |
| sort | Sort order | score desc |
| wt | Format: json or xml | xml |
| hl | Enable highlighting | false |
| Field | Type | Description |
|-------|------|-------------|
| id | string | DOI |
| title | string | Article title |
| author | array | Author names |
| abstract | string | Abstract text |
| body | string | Full text (large) |
| publication_date | date | Publication date |
| journal | string | Journal name |
| article_type | string | Article type |
| subject | array | Subject categories |
| score | float | Relevance score |
| Journal | Scope | |---------|-------| | PLOS ONE | Multidisciplinary | | PLOS Biology | Life sciences | | PLOS Medicine | Clinical medicine | | PLOS Genetics | Genetics and genomics | | PLOS Computational Biology | Computational biology | | PLOS Pathogens | Infectious disease | | PLOS Neglected Tropical Diseases | Tropical medicine |
import requests
BASE_URL = "https://api.plos.org/search"
def search_plos(query: str, rows: int = 20,
journal: str = None,
from_date: str = None,
fields: str = None) -> list:
"""Search PLOS open access articles."""
params = {
"q": query,
"wt": "json",
"rows": rows,
"fl": fields or "id,title,author,abstract,publication_date,journal,score",
}
fq_parts = []
if journal:
fq_parts.append(f'journal:"{journal}"')
if from_date:
fq_parts.append(
f"publication_date:[{from_date}T00:00:00Z TO NOW]"
)
if fq_parts:
params["fq"] = " AND ".join(fq_parts)
resp = requests.get(BASE_URL, params=params)
resp.raise_for_status()
data = resp.json()
results = []
for doc in data.get("response", {}).get("docs", []):
results.append({
"doi": doc.get("id"),
"title": doc.get("title"),
"authors": doc.get("author", []),
"date": doc.get("publication_date", "")[:10],
"journal": doc.get("journal"),
"abstract": (doc.get("abstract", [""])[0])[:300]
if isinstance(doc.get("abstract"), list)
else (doc.get("abstract", ""))[:300],
})
return results
def get_full_text(doi: str) -> str:
"""Retrieve full text body of a PLOS article."""
params = {
"q": f'id:"{doi}"',
"fl": "body",
"wt": "json",
}
resp = requests.get(BASE_URL, params=params)
resp.raise_for_status()
docs = resp.json().get("response", {}).get("docs", [])
return docs[0].get("body", "") if docs else ""
# Example: search PLOS Computational Biology
papers = search_plos(
"protein structure prediction",
journal="PLOS Computational Biology",
from_date="2024-01-01",
)
for p in papers:
print(f"[{p['date']}] {p['title']}")
print(f" DOI: {p['doi']}")
# Example: full-text search across all PLOS
papers = search_plos("body:reinforcement+learning AND title:robot")
for p in papers:
print(f"{p['title']} — {p['journal']}")
# Phrase proximity search (words within 5 of each other)
q=abstract:"machine learning"~5
# Boosted field search
q=title:"CRISPR"^2 OR abstract:"CRISPR"
# Wildcard search
q=title:neuro*
# Range query on dates
fq=publication_date:[2024-01-01T00:00:00Z TO 2024-12-31T23:59:59Z]
No formal rate limit, but PLOS requests courtesy delays of 1 request per second for bulk operations. No authentication needed.
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