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create_item

Add new bibliographic entries to Zotero by specifying item type, title, creators, and optional metadata like DOI, URL, or collections.

Instructions

Create a new item in Zotero

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
item_typeYes
titleYes
creatorsYes
dateNo
doiNo
urlNo
abstractNo
publicationNo
collectionsNo
tagsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • MCP tool registration for create_item.
    @mcp.tool(description="Create a new item in Zotero")
    def create_item(
        item_type: str,
        title: str,
        creators: list[dict],
        date: str = "",
        doi: str = "",
        url: str = "",
        abstract: str = "",
        publication: str = "",
        collections: list[str] | None = None,
        tags: list[str] | None = None,
    ) -> str:
        """Create a Zotero item. creators format: [{"type":"author","firstName":"...","lastName":"..."}]"""
        key = _get_client().create_item(
            item_type, title, creators, date, doi, url, abstract, publication,
            collections, tags,
        )
        return json.dumps({"key": key}, ensure_ascii=False)
  • Implementation of create_item logic in ZoteroClient.
    def create_item(
        self,
        item_type: str,
        title: str,
        creators: list[dict],
        date: str = "",
        doi: str = "",
        url: str = "",
        abstract: str = "",
        publication: str = "",
        collections: list[str] | None = None,
        tags: list[str] | None = None,
    ) -> str:
        """Create a new Zotero item. Returns the item key."""
        template = self.zot.item_template(item_type)
        template["title"] = title
        template["creators"] = creators
        if date:
            template["date"] = date
        if doi:
            template["DOI"] = doi
        if url:
            template["url"] = url
        if abstract:
            template["abstractNote"] = abstract
        if publication:
            pub_field = {
                "journalArticle": "publicationTitle",
                "conferencePaper": "conferenceName",
                "bookSection": "bookTitle",
            }.get(item_type, "publicationTitle")
            template[pub_field] = publication
        if collections:
            template["collections"] = collections
        if tags:
            template["tags"] = [{"tag": t} for t in tags]
    
        resp = self.zot.create_items([template])
        created = resp.get("successful", resp.get("success", {}))
        if created:
            key = list(created.values())[0] if isinstance(created, dict) else created[0]
            if isinstance(key, dict):
                return key.get("key", key.get("data", {}).get("key", ""))
            return str(key)
        raise RuntimeError(f"Failed to create item: {resp.get('failed', resp)}")
Behavior2/5

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

With no annotations, the description carries full burden but only states it creates an item without disclosing behavioral traits like permissions needed, whether it's idempotent, error handling, or what the output contains. It mentions Zotero as context but adds minimal operational insight.

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 a single, direct sentence with zero waste—it efficiently conveys the core action without unnecessary words. It's appropriately sized and front-loaded for quick comprehension.

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

Completeness3/5

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

Given 10 parameters with 0% schema coverage, no annotations, and an output schema (which reduces need to explain returns), the description is incomplete. It covers the basic purpose but lacks details on parameters, usage, and behavior needed for effective tool invocation.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate but adds no parameter information. It doesn't explain what 'item_type' entails, the format of 'creators', or the purpose of fields like 'collections' and 'tags', leaving parameters largely undocumented.

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

Purpose4/5

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

The description clearly states the action ('Create') and resource ('new item in Zotero'), making the purpose immediately understandable. It doesn't distinguish from siblings like 'create_item_from_doi' or 'create_collection', but it's not vague or tautological.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like 'create_item_from_doi' for DOI-based creation or 'import_bibtex' for batch imports. The description lacks context about prerequisites or typical use cases.

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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