LibreOffice MCP Tools

document_get_metadata

Extract document metadata including title, author, page count, word count, format, file size, and dates to understand document structure before reading content.

Instructions

Get metadata for an open document: title, author, page count, word count, format, file size, dates. Token-efficient: use this before reading document content to understand its size and structure.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "docId": "<docId>"
    },
    "name": "document_get_metadata"
  }
}

Input Schema

Name	Required	Description	Default
`docId`	Yes	Document handle returned by document_open

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Apr 21, 2026

TDQS

A4.4/5.0

Behavior4/5

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

No annotations are provided, so the description carries full burden. It effectively discloses key behavioral traits: it's a read-only operation (implied by 'Get'), requires an open document (via docId from document_open), and is 'Token-efficient' (a performance consideration). However, it doesn't mention error handling, rate limits, or authentication needs, leaving some gaps.

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?

Two concise sentences with zero waste: the first states purpose and lists metadata fields, the second provides usage guidance. It's front-loaded with essential information and appropriately sized for the tool's complexity.

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 tool's low complexity (1 parameter, 100% schema coverage, no output schema), the description is largely complete. It covers purpose, usage, and key behavioral aspects. A minor gap is the lack of output format details (e.g., structure of returned metadata), but this is partially mitigated by the listed metadata fields.

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?

Schema description coverage is 100%, with the docId parameter fully documented in the schema. The description adds no additional parameter details beyond what the schema provides (e.g., no examples or format specifics), so it meets the baseline of 3 without compensating further.

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 specific action ('Get metadata') and resource ('an open document'), listing concrete metadata fields (title, author, page count, etc.). It distinguishes from siblings like document_read_range or document_read_text by focusing on metadata rather than content.

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

Usage Guidelines5/5

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

Explicitly states when to use this tool ('use this before reading document content to understand its size and structure') and implies when not to use it (e.g., for content reading, use document_read_range or document_read_text instead). This provides clear context relative to sibling tools.

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