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grp-docx-mcp

grp-docx-mcp

by Arvindh95Censof
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_word_count

Return the word count of the open document body to track document length.

Instructions

Return the word count of the open document body.

Returns: {"word_count": int}

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_word_count"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.4

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations present, the description carries the full burden of behavioral disclosure. It correctly indicates a read-only operation and specifies the return format. However, it does not mention potential error conditions (e.g., missing open document) or performance implications, 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?

The description is extremely concise: one sentence plus a return format example. It is front-loaded with the core action, and every word is informative. There is no redundancy or unnecessary detail.

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 the tool's simplicity (no parameters, clear return type), the description is mostly complete. However, it could briefly mention that the document must be open, or reference related tools like 'get_statistics' for more comprehensive analysis. The omission of any usage context or constraints makes it slightly less than fully complete.

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 tool has no parameters, and the input schema is fully covered (100%). Per guidelines, when coverage is high, the baseline is 3. The description adds no parameter details because none exist, which is adequate but not exceptional.

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 ('Return') and resource ('word count of the open document body'), making the tool's purpose immediately obvious. It distinguishes itself from siblings like 'get_statistics' which might return multiple stats, and 'get_reading_time' which is a different metric.

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 such as 'get_statistics' (which likely includes word count) or 'get_body_text' (which could be used to manually count). The description lacks explicit when-to-use or when-not-to-use context.

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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