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grp-docx-mcp

grp-docx-mcp

by Arvindh95Censof
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

flatten_document

Accepts all tracked changes and removes revision markup, including formatting changes, to produce clean plain text without tracked-change metadata.

Instructions

Accept all tracked changes and remove all revision markup.

Accepts every w:ins / w:del and strips all w:rPrChange and w:pPrChange elements, leaving plain text with no tracked-change metadata.

Returns: {"changes_accepted": int, "formatting_changes_removed": 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": "flatten_document"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.4

TDQS

A4.1/5.0
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 of behavioral disclosure. It describes the changes made (accepting tracked changes, stripping formatting revision elements) but does not discuss side effects, irreversibility, prerequisites (e.g., document must have tracked changes), or idempotency. Some behavioral gaps remain.

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 highly concise, using two short paragraphs and a return value specification. Every sentence adds value: a clear summary, technical details on what is stripped, and the return format. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no parameters and an output schema that is explicitly described in the return value, the description is complete. It covers the tool's action, the specific XML transformations, and the return format. For a tool with no inputs, it provides sufficient context.

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?

There are no parameters, and the input schema is empty. The description does not need to add parameter information beyond what the schema provides. Schema coverage is 100%, so the baseline is 4. The description adds no unnecessary detail.

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's purpose with specific verbs ('accept all tracked changes' and 'remove all revision markup') and identifies the exact XML elements (w:ins, w:del, w:rPrChange, w:pPrChange). This distinguishes it from siblings like 'accept_all_changes' which may not strip formatting revisions.

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

Usage Guidelines3/5

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

The description implies when to use the tool (to finalize a document by accepting changes and removing all revision metadata) but does not explicitly state when not to use it or compare it to alternatives like 'accept_all_changes' or 'reject_all_changes'. It lacks explicit usage guidance.

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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