Skip to main content
Glama

batch_update_documents

DestructiveIdempotent

Update multiple documents with different changes in one batch operation. Each change is processed sequentially, with automatic error handling and rate limiting.

Instructions

    Updates multiple documents with different changes.

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

    Use this tool when you need to:
    - Update multiple documents with different changes
    - Batch edit document titles or content
    - Append content to multiple documents

    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:
        updates: List of update specifications

    Returns:
        Summary of batch operation with
        success/failure details
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
updatesYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Beyond annotations (destructive, idempotent), the description adds sequential processing, error continuation ('continuing even if individual operations fail'), and automatic rate limiting. This provides useful behavioral context.

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 somewhat lengthy with a tangential note about Mermaid diagrams. While front-loaded with the main purpose, it contains some verbose formatting that could be tightened.

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?

Covers purpose, usage, behavior, and batch size. With an output schema present, return description is acceptable. However, it lacks details on failure handling specifics and does not explain the role of the 'append' parameter beyond what schema provides.

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%. The description only says 'List of update specifications' without adding detail. The schema itself has descriptions on each field, but the description text does not compensate for the lack of parameter documentation.

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 starts with a clear verb+resource: 'Updates multiple documents with different changes.' It distinguishes from siblings like 'update_document' (single) and batch operations for create/delete/archive.

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?

Lists explicit use cases (batch edit titles/content, append) and provides a recommended batch size. However, it does not explicitly state when not to use it or mention alternatives like sequential single updates.

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