mcp-document-intelligence

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suggest_structure

Suggests a folder structure from analyzed documents by grouping files by year, category, and company to organize local files.

Instructions

Suggest an intelligent folder structure based on analyzed documents — groups by year, category, and company.

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": {
      "documents": "<documents>"
    },
    "name": "suggest_structure"
  }
}

Input Schema

Name	Required	Description	Default
`documents`	Yes	Array of analyzed document objects (from analyze_folder)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv4.6.0Nov 6, 2026

TDQS

A3.6/5.0

Behavior3/5

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

No annotations are provided, so the description must carry behavioral disclosure. 'Suggest' implies an advisory, non-mutating operation, and the grouping criteria add useful context, but the description does not explicitly state that no files are moved or modified, nor does it clarify the response shape.

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 definition is a single, front-loaded sentence with no wasted wording. It states the action, the basis for the suggestion, and the grouping criteria efficiently.

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?

For a simple one-parameter tool with full schema coverage and no output schema, the description is largely complete: it explains what is produced and the grouping logic. It could be stronger if it clarified its relationship to organization tools like auto_organize, but the core information is present.

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%, so the schema already documents the single documents parameter. The description reinforces that documents are 'analyzed' but adds no additional parameter semantics beyond what the schema provides, making the baseline score appropriate.

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?

The description states a specific verb and resource: 'Suggest' a 'folder structure.' It also specifies the grouping behavior by year, category, and company. However, it does not distinguish this from siblings such as auto_organize or batch_organize, so it falls short of the top score.

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 phrase 'based on analyzed documents' and the schema note that documents come from analyze_folder imply the prerequisite input. But there is no explicit guidance on when to choose suggest_structure instead of auto_organize, batch_organize, or other sibling tools.

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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