Skip to main content
Glama

batch_create_documents

DestructiveIdempotent

Creates multiple documents in one operation; handles rate limiting and partial failures. Use for bulk imports or setting up document structures.

Instructions

    Creates multiple documents in a single batch
    operation.

    This tool processes each creation sequentially,
    continuing even if individual operations fail.
    Rate limiting is handled automatically.

    Use this tool when you need to:
    - Create multiple documents at once
    - Bulk import content into collections
    - Set up document structures efficiently

    Note: For Mermaid diagrams, use ```mermaidjs
    (not ```mermaid) as the code fence language
    identifier for proper rendering.

    Recommended batch size: 10-50 documents per
    operation

    Args:
        documents: List of document specifications

    Returns:
        Summary of batch operation with created
        document IDs and success/failure details
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
documentsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Beyond the annotations (readOnlyHint=false, destructiveHint=true, idempotentHint=true), the description adds that operations are sequential and continue on failure, rate limiting is automatic, and recommends batch size. Adds useful context without contradicting annotations.

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

Conciseness3/5

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

The description is moderately concise but includes an out-of-place note about Mermaid code fence syntax, which adds unnecessary detail. Could be streamlined.

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?

Given the single parameter with nested object, the description covers purpose, usage, behavior, and return summary. It lacks detail on failure behavior beyond 'continuing' but is generally complete for a well-annotated tool.

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

Parameters3/5

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

The description mentions 'documents: List of document specifications' but does not elaborate on sub-fields; the input schema already describes each property. The recommended batch size adds value, but overall parameter description is minimal.

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?

The description clearly states the verb 'creates' and the resource 'multiple documents in a single batch operation'. It distinguishes from siblings like 'create_document' by specifying batch behavior.

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?

The description lists explicit use cases (create multiple documents at once, bulk import, etc.) and implies that for single documents one should use alternatives. It provides good context, though could explicitly mention when not to use.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Vortiago/mcp-outline'

If you have feedback or need assistance with the MCP directory API, please join our Discord server