> pyzotero

Interact with Zotero reference management libraries using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3. Use this skill when working with Zotero libraries programmatically, managing bibliographic references, exporting citations, searching library contents, uploading PDF attachments, or building research automation workflows that integrate with Zotero.

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SKILL.mdpyzotero

Pyzotero

Pyzotero is a Python wrapper for the Zotero API v3. Use it to programmatically manage Zotero libraries: read items and collections, create and update references, upload attachments, manage tags, and export citations.

Authentication Setup

Required credentials — get from https://www.zotero.org/settings/keys:

Store credentials in environment variables or a .env file:

ZOTERO_LIBRARY_ID=your_user_id
ZOTERO_API_KEY=your_api_key
ZOTERO_LIBRARY_TYPE=user  # or "group"

See references/authentication.md for full setup details.

Installation

uv add pyzotero
# or with CLI support:
uv add "pyzotero[cli]"

Quick Start

from pyzotero import Zotero

zot = Zotero(library_id='123456', library_type='user', api_key='ABC1234XYZ')

# Retrieve top-level items (returns 100 by default)
items = zot.top(limit=10)
for item in items:
    print(item['data']['title'], item['data']['itemType'])

# Search by keyword
results = zot.items(q='machine learning', limit=20)

# Retrieve all items (use everything() for complete results)
all_items = zot.everything(zot.items())

Core Concepts

  • A Zotero instance is bound to a single library (user or group). All methods operate on that library.
  • Item data lives in item['data']. Access fields like item['data']['title'], item['data']['creators'].
  • Pyzotero returns 100 items by default (API default is 25). Use zot.everything(zot.items()) to get all items.
  • Write methods return True on success or raise a ZoteroError.

Reference Files

FileContents
references/authentication.mdCredentials, library types, local mode
references/read-api.mdRetrieving items, collections, tags, groups
references/search-params.mdFiltering, sorting, search parameters
references/write-api.mdCreating, updating, deleting items
references/collections.mdCollection CRUD operations
references/tags.mdTag retrieval and management
references/files-attachments.mdFile retrieval and attachment uploads
references/exports.mdBibTeX, CSL-JSON, bibliography export
references/pagination.mdfollow(), everything(), generators
references/full-text.mdFull-text content indexing and retrieval
references/saved-searches.mdSaved search management
references/cli.mdCommand-line interface usage
references/error-handling.mdErrors and exception handling

Common Patterns

Fetch and modify an item

item = zot.item('ITEMKEY')
item['data']['title'] = 'New Title'
zot.update_item(item)

Create an item from a template

template = zot.item_template('journalArticle')
template['title'] = 'My Paper'
template['creators'][0] = {'creatorType': 'author', 'firstName': 'Jane', 'lastName': 'Doe'}
zot.create_items([template])

Export as BibTeX

zot.add_parameters(format='bibtex')
bibtex = zot.top(limit=50)
# bibtex is a bibtexparser BibDatabase object
print(bibtex.entries)

Local mode (read-only, no API key needed)

zot = Zotero(library_id='123456', library_type='user', local=True)
items = zot.items()

> related_skills --same-repo

> writing

Use this skill to create high-quality academic papers, literature reviews, grant proposals, clinical reports, and other research and scientific documents backed by comprehensive research and real, verifiable citations. Use this skill whenever the user asks for written output such as a report, paper...etc.

> xlsx

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my

> scikit-learn

Machine learning in Python with scikit-learn. Use when working with supervised learning (classification, regression), unsupervised learning (clustering, dimensionality reduction), model evaluation, hyperparameter tuning, preprocessing, or building ML pipelines. Provides comprehensive reference documentation for algorithms, preprocessing techniques, pipelines, and best practices.

> pytorch-lightning

Deep learning framework (PyTorch Lightning). Organize PyTorch code into LightningModules, configure Trainers for multi-GPU/TPU, implement data pipelines, callbacks, logging (W&B, TensorBoard), distributed training (DDP, FSDP, DeepSpeed), for scalable neural network training.

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first seenMar 17, 2026
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┌ repo

K-Dense-AI/claude-scientific-skills
by K-Dense-AI
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┌ tags

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