io.github.WiliamRosa/cosmos-semantic

query

Request governed business metrics with user policies applied and retrieve up to 200 rows for consistent analysis across databases.

Instructions

Run a metrics request with the user's policies applied. Returns at most 200 rows.

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": {
      "metrics": "<metrics>"
    },
    "name": "query"
  }
}

Input Schema

Name	Required	Description	Default
`as_of`	No
`limit`	No
`filters`	No
`metrics`	Yes
`order_by`	No
`dimensions`	No
`rules_as_of`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 5, 2026

TDQS

C2.7/5.0

Behavior3/5

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

With no annotations provided, the description carries the full behavioral burden. It usefully discloses that user policies are applied and that results are capped at 200 rows, but it does not state whether the operation is read-only, what authentication is required, or how policy failures are surfaced.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences and front-loads the main action before the row-limit detail. Every sentence earns its place, though the brevity is also the source of the definition's incompleteness.

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

Completeness2/5

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 explained. However, for a seven-parameter query tool with no annotations and no schema descriptions, the definition is far too thin on parameter meaning, usage alternatives, and behavioral constraints.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has seven parameters with 0% description coverage, and the description does not explain any of them. Terms like metrics, as_of, limit, filters, order_by, dimensions, and rules_as_of are left entirely to the schema's bare titles and types.

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 clear verb and resource: it runs a metrics request with the user's policies applied. It does not distinguish this tool from siblings such as explain, show_sql, or search_concepts, but the core action is understandable.

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

Usage Guidelines2/5

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

There is no explicit guidance on when to use this tool versus explain, show_sql, or search_concepts. The description implies it is the execution tool for metrics, but leaves all routing decisions to inference.

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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