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report_schema_detail

Read-only

Get full details for a specific analytics view.

Returns all measures, dimensions, and segments with their names, types, and descriptions. Use report_schema first to discover available views, then call this with the view name to get queryable fields for report_query.

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": {
      "view": "<view>"
    },
    "name": "report_schema_detail"
  }
}

Input Schema

NameRequiredDescriptionDefault
viewYesView name from report_schema, e.g. "billing_overview"

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds real value beyond that by describing the payload shape (measures/dimensions/segments with metadata), which matters because no output schema exists. It stops short of noting behavior for an unknown/invalid view name or whether custom dimensions are included.

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?

Three short sentences, front-loaded with purpose, then return contents, then workflow routing. No filler or redundant restatement of the tool name.

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?

With a single required parameter, no output schema, and safe-read annotations, the definition covers what an agent needs: purpose, input provenance, return contents, and next-step tool. The only gaps are edge-case behavior (invalid view name, empty result) and whether the listing is exhaustive or paginated.

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 coverage is 100% and the schema already gives the example 'billing_overview', so the description adds little parameter-level detail. It reinforces the provenance of the value (from report_schema), but that constraint is also present in the schema's own property description, so the baseline 3 applies.

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 first sentence names a specific verb and resource ('Get full details for a specific analytics view'), and the following sentence enumerates exactly what is returned (measures, dimensions, segments with names, types, descriptions). This clearly separates it from report_schema, which only discovers view names.

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

Usage Guidelines5/5

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

The description prescribes an explicit two-step workflow: call report_schema first to discover views, then this tool with the view name. It also states the downstream consumer ('queryable fields for report_query'), so the agent knows both prerequisites and where the output goes.

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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