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generate_sql

Converts natural-language questions into validated SELECT SQL queries without executing them, enabling safe data exploration and query drafting.

Instructions

Generate one validated SELECT from a natural-language question, without executing 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": {
      "connection_id": "<connection_id>",
      "question": "<question>"
    },
    "name": "generate_sql"
  }
}

Input Schema

Name	Required	Description	Default
`question`	Yes
`connection_id`	Yes

Output Schema

Name	Required	Description	Default
`message`	Yes
`outcome`	Yes	Terminal outcome of one SQL generation attempt.
`question`	Yes
`generated`	No
`error_code`	No
`clarification`	No
`connection_id`	Yes
`contract_version`	No		1.0.0

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.9.0Aug 5, 2026

TDQS

A3.8/5.0

Behavior3/5

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

With no annotations, the description carries the transparency burden. It discloses the key non-execution behavior, but does not mention other behavioral aspects such as validation failure handling, whether the SQL is returned as a string, or permission/rate-limit concerns. The existence of an output schema reduces the need to describe return structure, but additional detail would improve transparency.

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, front-loaded sentence with no filler. Every word contributes to the core meaning: generation, single SELECT, validation, natural-language source, and non-execution.

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?

For a simple 2-parameter tool with an output schema, the description covers the primary purpose but lacks explicit parameter clarification and usage alternatives relative to many siblings. It is minimally complete but not richly contextual.

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?

Input schema has zero parameter descriptions, so the tool description must compensate. It implicitly maps 'question' to the natural-language question, but connection_id is not mentioned at all. The description adds only partial meaning and fails to clarify the role of connection_id in generating SQL.

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 clearly states the tool generates one validated SELECT from a natural-language question and explicitly says it does not execute it. This specific verb-resource pair ('generate ... SELECT') and the execution constraint distinguish it from siblings like generate_and_execute_query and validate_sql.

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 phrase 'without executing it' provides clear context for when this tool is appropriate versus siblings that also handle execution or validation. However, it does not explicitly name alternatives or state when-not-to-use, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.