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docx-mcp

docx-mcp

by dboles99
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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check_docx_term_variants

Count occurrences of specified term variants in a DOCX's accepted text to identify which spelling is used and where.

Instructions

Count occurrences of each term across all accepted text in a DOCX.

Useful for consistency checks, for example passing ["cyber security", "cybersecurity"] to see which spelling is used and where.

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": {
      "path": "<path>",
      "terms": "<terms>"
    },
    "name": "check_docx_term_variants"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes
termsYes
case_sensitiveNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full behavioral burden. It does disclose one meaningful trait beyond the signature — that only "accepted text" is scanned, implying rejected/tracked-change content is excluded — but says nothing about read-only safety, matching semantics, or performance.

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 short sentences, the core behavior is front-loaded, and the example immediately reinforces it. Nothing is padded or redundant.

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?

An output schema exists, so return values need not be described. However, with zero annotation coverage and zero schema parameter descriptions, the undefined semantics of `case_sensitive` and the scope of "accepted text" leave real gaps for a three-parameter tool.

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 0%, so the description should compensate for all three parameters. It clarifies the shape and intent of `terms` via a worked example, but `path` and especially `case_sensitive` are left with no explanation of matching behavior or default effects.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: count occurrences of each term across all accepted text in a DOCX. The plural "count occurrences of each term" implicitly separates it from the singular sibling find_docx_term, but no sibling is named explicitly.

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?

Gives a concrete usage scenario (passing ["cyber security", "cybersecurity"] to check spelling consistency), which is enough for an agent to recognize the intended context. It offers no explicit exclusions or named alternatives, so it falls short of a 5.

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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