Best use case
figshare-api is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Research data sharing and repository
Teams using figshare-api should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/figshare-api/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How figshare-api Compares
| Feature / Agent | figshare-api | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Research data sharing and repository
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Figshare API Guide
## Overview
Figshare is a cloud-based research data management platform that allows researchers to store, share, and discover research outputs including datasets, figures, media, papers, posters, and fileset collections. Every item uploaded to Figshare receives a citable DOI and is stored in a FAIR-compliant manner, making research outputs findable, accessible, interoperable, and reusable.
The Figshare API provides comprehensive programmatic access to the repository, enabling researchers and institutions to automate data publishing, integrate with research workflows, and build custom discovery interfaces. The platform supports versioning, embargo periods, and flexible access controls for both public and private research data.
Researchers, data managers, institutional repository administrators, and research infrastructure developers use the Figshare API to automate deposit workflows, harvest metadata for institutional dashboards, build data discovery tools, and integrate research data management into existing laboratory information management systems. Figshare serves over 150 institutions worldwide and hosts millions of research outputs.
## Authentication
Authentication via personal access token is required for write operations and accessing private content. Read access to public content is available without authentication but has lower rate limits.
1. Log in to Figshare at https://figshare.com/
2. Navigate to **Applications** in your account settings
3. Create a **Personal Token** with desired permissions
4. Include the token in the `Authorization` header
```bash
curl -H "Authorization: token YOUR_FIGSHARE_TOKEN" "https://api.figshare.com/v2/account/articles"
```
Public endpoints can be accessed without a token for browsing published content.
## Core Endpoints
### articles: Search and Retrieve Articles
Search the public Figshare repository for published articles (datasets, figures, papers, media, and other item types).
- **URL**: `GET https://api.figshare.com/v2/articles`
- **Parameters**:
| Parameter | Type | Required | Description |
|----------------|--------|----------|--------------------------------------------------------|
| search_for | string | No | Free-text search query |
| item_type | int | No | Item type filter (1=figure, 2=media, 3=dataset, etc.) |
| published_since| string | No | Filter by date (YYYY-MM-DD format) |
| order | string | No | Sort: `published_date`, `modified_date`, `views` |
| order_direction| string | No | `asc` or `desc` |
| page | int | No | Page number (default 1) |
| page_size | int | No | Results per page (default 10, max 1000) |
- **Example**:
```bash
curl -X POST "https://api.figshare.com/v2/articles/search" \
-H "Content-Type: application/json" \
-d '{"search_for": "genomics CRISPR", "item_type": 3, "page_size": 5}'
```
- **Response**: Returns array of article objects with `id`, `title`, `doi`, `url`, `published_date`, `description`, `defined_type_name`, `categories`, `tags`, `authors`, `files` (with download URLs), and `citation`.
### datasets: Manage Research Datasets
Retrieve and manage dataset-specific content in Figshare. Datasets are a specialized article type with additional support for large file collections.
- **URL**: `GET https://api.figshare.com/v2/articles/{article_id}`
- **Parameters**:
| Parameter | Type | Required | Description |
|------------|------|----------|------------------------------------|
| article_id | int | Yes | The Figshare article/dataset ID |
- **Example**:
```bash
# Get a specific dataset by ID
curl "https://api.figshare.com/v2/articles/12345678"
# List files in a dataset
curl "https://api.figshare.com/v2/articles/12345678/files"
```
- **Response**: Returns complete article object with `id`, `title`, `doi`, `description`, `authors`, `categories`, `tags`, `files` (array with `name`, `size`, `download_url`, `computed_md5`), `license`, `version`, `is_embargoed`, and `custom_fields`.
## Rate Limits
Rate limits vary based on authentication status and endpoint. Authenticated requests generally allow up to 100 requests per minute. Unauthenticated requests are limited to approximately 10 requests per minute. The API returns HTTP 429 with a `Retry-After` header when limits are exceeded. For bulk data harvesting, Figshare provides OAI-PMH endpoints at `https://api.figshare.com/v2/oai` which are more suitable for large-scale metadata collection.
## Common Patterns
### Search for Datasets in a Research Area
Find publicly available datasets matching specific research topics:
```python
import requests
payload = {
"search_for": "single cell RNA-seq",
"item_type": 3, # datasets only
"page_size": 20,
"order": "published_date",
"order_direction": "desc"
}
resp = requests.post("https://api.figshare.com/v2/articles/search", json=payload)
results = resp.json()
for item in results:
print(f"{item['title']}")
print(f" DOI: {item['doi']}")
print(f" Published: {item['published_date']}")
print()
```
### Upload a Dataset Programmatically
Automate data deposit for reproducible research workflows:
```python
import requests
TOKEN = os.environ["FIGSHARE_API_TOKEN"]
headers = {"Authorization": f"token {TOKEN}", "Content-Type": "application/json"}
# Step 1: Create a new article
article_data = {
"title": "Supplementary Data for Analysis of Gene Expression",
"defined_type": "dataset",
"description": "RNA-seq counts and metadata for the analysis.",
"tags": ["RNA-seq", "gene expression"],
"categories": [69] # Genetics category
}
resp = requests.post("https://api.figshare.com/v2/account/articles",
headers=headers, json=article_data)
article_url = resp.json()["location"]
# Step 2: Upload file
article = requests.get(article_url, headers=headers).json()
print(f"Created article ID: {article['id']}, DOI will be assigned on publish")
```
### Harvest Institutional Outputs via OAI-PMH
Collect metadata from all Figshare items in an institution's repository:
```bash
curl "https://api.figshare.com/v2/oai?verb=ListRecords&metadataPrefix=oai_dc&set=institution_123"
```
## References
- Official API documentation: https://docs.figshare.com/
- Figshare homepage: https://figshare.com/
- API endpoint reference: https://docs.figshare.com/#figshare_documentation_api_description
- OAI-PMH endpoint: https://docs.figshare.com/#oai_pmhRelated Skills
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