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grp-docx-mcp

grp-docx-mcp

by Arvindh95Censof
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

set_run_language

Assign a BCP-47 language code to a specific text run within a paragraph to enable correct spell-checking for that portion of the document.

Instructions

Set the language on a run for spell-checking purposes.

Args: para_id: paraId of the target paragraph. run_idx: Zero-based index of the run. language_code: BCP-47 language code (e.g., "en-US", "fr-FR", "de-DE").

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": {
      "para_id": "<para_id>",
      "run_idx": "<run_idx>",
      "language_code": "<language_code>"
    },
    "name": "set_run_language"
  }
}

Input Schema

NameRequiredDescriptionDefault
para_idYes
run_idxYes
language_codeYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.4

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the full burden. It states it sets language for spell-checking, hinting at mutation, but does not disclose side effects, permissions, or reversibility. This is adequate but not thorough.

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 and a bulleted list of parameters. Every word is necessary, no fluff, and the purpose is front-loaded.

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 has an output schema (not shown) and low complexity, the description covers the primary behavior and parameter semantics. It does not address error handling or validity checks, but is generally complete for its purpose.

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

Parameters4/5

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

With 0% schema description coverage, the description compensates by providing clear explanations for all three parameters: para_id, run_idx (zero-based index), and language_code with BCP-47 examples. This adds meaningful context beyond names and types.

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 tool sets the language on a run for spell-checking purposes, using a specific verb and resource. It distinguishes itself from sibling tools like set_run_color or set_document_language by focusing on language at the run level.

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 implies usage for spell-checking context but does not explicitly state when to use this tool versus alternatives like set_document_language. The purpose is clear enough for an AI to infer, but lacks explicit when-not or alternatives.

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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