io.github.WiliamRosa/cosmos-semantic

show_sql

Generates and displays the SQL query for requested metrics, dimensions, and filters without running it, so you can inspect or validate the query before execution.

Instructions

Show the SQL the engine generates for a request, without running it.

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": "show_sql"
  }
}

Input Schema

Name	Required	Description	Default
`filters`	No
`metrics`	Yes
`dimensions`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 5, 2026

TDQS

B3.3/5.0

Behavior3/5

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

With zero annotations, the description carries the full burden and does disclose the most important behavioral trait: it is a dry run that generates but does not execute SQL, so no side effects occur. It says nothing about how invalid metric/dimension names are handled, whether errors are raised or reported, or any permission requirements.

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?

One sentence, front-loaded with the action and immediately followed by the most decision-relevant constraint. Nothing is wasted and nothing needs restructuring.

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. Still, for a query-builder tool with three fully undocumented parameters, the definition leaves an agent guessing about identifier formats and error behavior, which is more than a minor omission.

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

Parameters2/5

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

Schema description coverage is 0% and the three parameters (metrics, filters, dimensions) are undocumented in the schema. The description says only 'for a request', adding no meaning about what metric/dimension identifiers look like, the expected format of filters, or that metrics is required — a clear gap the description should fill.

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 concrete verb and resource ('Show the SQL the engine generates') plus the crucial scope qualifier 'for a request, without running it'. This implicitly separates it from the sibling 'query', which presumably executes, though 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 Guidelines3/5

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

The 'without running it' clause implies the use case: inspecting generated SQL before execution. However, there is no explicit when-to-use/when-not statement, no mention of choosing this over 'explain' or 'query', and no note that 'metrics' is mandatory.

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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