skills/43-wentorai-research-plugins/skills/literature/fulltext/osf-api/SKILL.md
Manage open science projects and preprints via the OSF REST API
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research osf-apiInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
The Open Science Framework by the Center for Open Science provides infrastructure for the entire research lifecycle — project management, file storage, preprint hosting, and registrations. The API enables search, project creation, file management, and preprint discovery across OSF Preprints, PsyArXiv, SocArXiv, and 25+ community preprint servers. Free, no auth for read access.
https://api.osf.io/v2
# Search across all OSF content
curl "https://api.osf.io/v2/search/?q=replication+crisis&page[size]=20"
# Search preprints
curl "https://api.osf.io/v2/preprints/?filter[q]=machine+learning&page[size]=20"
# Filter by preprint provider
curl "https://api.osf.io/v2/preprints/?filter[provider]=psyarxiv&filter[q]=cognitive+bias"
# Search registrations (pre-registered studies)
curl "https://api.osf.io/v2/registrations/?filter[q]=randomized+controlled+trial"
# Get public projects
curl "https://api.osf.io/v2/nodes/?filter[public]=true&filter[q]=neuroimaging"
# Get project details
curl "https://api.osf.io/v2/nodes/{node_id}/"
# Get project files
curl "https://api.osf.io/v2/nodes/{node_id}/files/"
# Get project contributors
curl "https://api.osf.io/v2/nodes/{node_id}/contributors/"
| Provider | Filter | Disciplines |
|----------|--------|-------------|
| OSF Preprints | osf | Multidisciplinary |
| PsyArXiv | psyarxiv | Psychology |
| SocArXiv | socarxiv | Social sciences |
| EarthArXiv | eartharxiv | Earth sciences |
| BioHackrXiv | biohackrxiv | Bioinformatics |
| engrXiv | engrxiv | Engineering |
| MedArXiv | medarxiv | Medical sciences |
| NutriXiv | nutrixiv | Nutrition |
| Parameter | Description | Example |
|-----------|-------------|---------|
| filter[q] | Text search | filter[q]=open+data |
| filter[provider] | Preprint server | filter[provider]=psyarxiv |
| filter[subjects] | Subject filter | Subject taxonomy ID |
| filter[date_created] | Date filter | filter[date_created][gte]=2024-01-01 |
| page[size] | Results per page (max 100) | page[size]=50 |
| page | Page number | page=2 |
{
"data": [
{
"id": "abc12",
"type": "preprints",
"attributes": {
"title": "Replication of the Ego Depletion Effect",
"description": "We attempted to replicate...",
"date_created": "2024-06-15T10:00:00Z",
"date_published": "2024-06-16T08:00:00Z",
"doi": "10.31234/osf.io/abc12",
"is_published": true,
"subjects": [["Social and Behavioral Sciences", "Psychology"]],
"tags": ["replication", "ego depletion"]
},
"relationships": {
"contributors": {"links": {"related": {"href": "..."}}},
"primary_file": {"links": {"related": {"href": "..."}}}
}
}
]
}
import requests
BASE_URL = "https://api.osf.io/v2"
def search_preprints(query: str, provider: str = None,
page_size: int = 20) -> list:
"""Search OSF preprints across providers."""
params = {
"filter[q]": query,
"page[size]": page_size,
}
if provider:
params["filter[provider]"] = provider
resp = requests.get(f"{BASE_URL}/preprints/", params=params)
resp.raise_for_status()
data = resp.json()
results = []
for item in data.get("data", []):
attrs = item.get("attributes", {})
results.append({
"id": item.get("id"),
"title": attrs.get("title"),
"description": (attrs.get("description") or "")[:300],
"doi": attrs.get("doi"),
"date": attrs.get("date_published", "")[:10],
"tags": attrs.get("tags", []),
"url": f"https://osf.io/{item.get('id')}/",
})
return results
def search_registrations(query: str,
page_size: int = 20) -> list:
"""Search pre-registered studies on OSF."""
params = {
"filter[q]": query,
"page[size]": page_size,
}
resp = requests.get(f"{BASE_URL}/registrations/", params=params)
resp.raise_for_status()
data = resp.json()
results = []
for item in data.get("data", []):
attrs = item.get("attributes", {})
results.append({
"id": item.get("id"),
"title": attrs.get("title"),
"description": (attrs.get("description") or "")[:300],
"date_registered": attrs.get("date_registered", "")[:10],
"registration_schema": attrs.get("registration_supplement"),
})
return results
def get_project_files(node_id: str) -> list:
"""List files in an OSF project."""
resp = requests.get(f"{BASE_URL}/nodes/{node_id}/files/")
resp.raise_for_status()
data = resp.json()
providers = []
for item in data.get("data", []):
attrs = item.get("attributes", {})
providers.append({
"provider": attrs.get("provider"),
"name": attrs.get("name"),
})
return providers
# Example: search psychology preprints
preprints = search_preprints("cognitive load", provider="psyarxiv")
for p in preprints[:5]:
print(f"[{p['date']}] {p['title']}")
print(f" DOI: {p['doi']}")
# Example: find pre-registered clinical trials
regs = search_registrations("randomized placebo")
for r in regs[:5]:
print(f"[{r['date_registered']}] {r['title']}")
tools
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
tools
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".
tools
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
tools
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".