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Create or update Zotero items

zotero_create_items

Create or update Zotero library items in batches, with automatic validation. Invalid items block the entire write, ensuring data integrity before syncing to the cloud API.

Instructions

Create new items or update existing ones in a single batch (the server auto-chunks into groups of 50). items is an ARRAY of item-data objects; each object has itemType as a plain string (e.g. "journalArticle", "book", "preprint", "report") plus its valid fields, creators (each {creatorType, firstName, lastName} or {creatorType, name}), tags ([{tag}]), and collections (array of 8-char collection keys). To UPDATE an existing item, also include its key and current version; to CREATE, omit both. Every item is validated against the Zotero schema before anything is sent — if any item is invalid, nothing is written and the problems are returned. Use zotero_schema to discover valid fields/creator types for an itemType. Writes go to the cloud Web API (requires ZOTERO_API_KEY).

Example:

{"items": [{"itemType": "journalArticle", "title": "The Role of Metadata in Machine Learning", "creators": [{"creatorType": "author", "firstName": "Ada", "lastName": "Lovelace"}], "date": "2024-01-15", "DOI": "10.1234/example.5678", "tags": [{"tag": "ml"}], "collections": ["ABCD1234"]}]}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
itemsYesArray of Zotero item-data objects (itemType + fields; include key+version to update). Example: {"items":[{"itemType":"journalArticle","title":"The Role of Metadata in Machine Learning","creators":[{"creatorType":"author","firstName":"Ada","lastName":"Lovelace"}],"date":"2024-01-15","DOI":"10.1234/example.5678","tags":[{"tag":"ml"}],"collections":["ABCD1234"]}]}
library_idNo
library_typeNo
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite annotations only indicating not read-only and open-world, the description discloses all-or-nothing schema validation, no partial writes on invalid items, server-side chunking into groups of 50, cloud Web API writes, and ZOTERO_API_KEY requirement. This substantially exceeds annotation information and does not contradict it.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but well-structured, front-loading the core purpose and batching fact, then item-data semantics, update/create rules, validation behavior, and auth requirement. The example JSON is compact and directly illustrates the format without unnecessary prose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a batch create/update tool with no output schema, the description covers purpose, data shapes, update semantics, validation, batching, and auth. Minor gaps remain: return/response shape beyond 'problems are returned' and how library_id/library_type affect the target library are not addressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The `items` parameter is richly described: itemType as plain string, creator/tag/collection shapes, update key/version semantics, and validation. However, `library_id` and `library_type` are not explained in the description, and schema description coverage is only 33%, so the parameter semantics are incomplete despite strong coverage of the main parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description opens with a specific action: 'Create new items or update existing ones in a single batch,' naming the resource (Zotero items), operation (create/update), and batching scope. This clearly differentiates it from single-item siblings such as zotero_update_item.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit create-vs-update rules: include `key` and current `version` to update, omit both to create. It also points to zotero_schema for valid fields/creator types, but does not explicitly contrast this batch tool with zotero_update_item or state when to prefer one over the other.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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