zotero-code-execution

🥈Silver

Zotero Code Execution enables efficient multi-strategy search within Zotero using code execution patterns. Researchers and operations teams benefit from automated bibliographic searches, semantic tagging, and data extraction. It connects to Zotero MCP and integrates with Python workflows for enhanced research automation.

2210Updated 1w ago

Intermediate30min to implementautomation

Saves ~180 min per use

Quick InstallView Source

git clone https://github.com/kerim/zotero-code-execution.git

Works with:

Claude

Overview

About This Skill

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/kerim/zotero-code-execution

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

I need to automate a bibliographic search in Zotero for [COMPANY] in the [INDUSTRY] sector. Use the Zotero Code Execution skill to create a Python script that searches for [KEYWORD] in titles and abstracts, then extracts and organizes the data into a CSV file. Include semantic tagging for [TAG1], [TAG2], and [TAG3].

Example Output

```python
# Zotero Code Execution Script
# Search Parameters
keywords = ['[KEYWORD]']
tags = ['[TAG1]', '[TAG2]', '[TAG3]']

# Initialize Zotero MCP
from zotero_mcp import ZoteroMCP
zotero = ZoteroMCP(api_key='[API_KEY]')

# Execute Search
search_results = zotero.search(keywords=keywords, tags=tags)

# Extract and Organize Data
data = []
for item in search_results:
    data.append({
        'title': item['title'],
        'author': item['creators'],
        'year': item['date'],
        'abstract': item['abstractNote'],
        'tags': item['tags']
    })

# Save to CSV
import csv
with open('[OUTPUT_FILE].csv', 'w', newline='') as csvfile:
    fieldnames = ['title', 'author', 'year', 'abstract', 'tags']
    writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
    writer.writeheader()
    writer.writerows(data)

print(f'Search completed. Data saved to {OUTPUT_FILE}.csv')
```