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Dimension Values

dimension_values
Read-onlyIdempotent

List the valid codes/labels for one dimension of a table (a sub-endpoint such as "Periods" or a region/category dimension key, as named in the table root or table_dimensions).

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "table": "37296eng",
      "dimension": "Periods"
    },
    "name": "dimension_values"
  }
}

Input Schema

NameRequiredDescriptionDefault
topNoMax rows (default 100).
tableYesCBS table id, e.g. "37296eng".
dimensionYesDimension endpoint name, e.g. "Periods", "CaribbeanNetherlands".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "dimension": "Periods",
      +    "table": "37296eng"
      +  },
      +  {
      +    "dimension": "RegionCode",
      +    "table": "37296eng",
      +    "top": 50
      +  }
      +]
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds that the tool returns codes/labels and that dimension is a sub-endpoint, providing useful behavioral context beyond the annotations. No contradictions.

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 a single, well-structured sentence that front-loads the action and resource. No unnecessary words or restatements.

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?

For a simple listing tool with fully described parameters and strong annotations, the description is complete. It states what the tool returns (codes/labels), clarifies the dimension parameter, and references sibling tools for context, making it fully sufficient for selection and invocation.

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?

Schema description coverage is 100%, so baseline is 3. The description adds semantic meaning for the 'dimension' parameter by explaining it is a sub-endpoint named in the table root or table_dimensions, which helps clarify how to fill the parameter correctly.

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 uses a specific verb ('List') and identifies the resource ('valid codes/labels for one dimension of a table'). It clearly distinguishes from sibling tools like table_dimensions (which lists dimensions) and get_data (which retrieves data) by focusing on a single dimension's values.

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 explicitly mentions 'as named in the table root or table_dimensions', implying that users should first identify dimensions via table_dimensions or table root. This provides clear context for when to use this tool, though it does not explicitly exclude alternative 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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