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rog0x

mcp-database-tools

by rog0x

sql_explain

Explains any SQL query in plain English, breaking down tables, columns, and conditions, with optimization tips for clearer understanding.

Instructions

Take a SQL query and explain what it does in plain English, step by step. Identifies tables, columns, conditions, and provides optimization tips.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYesThe SQL query to explain
Behavior3/5

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

With no annotations provided, the description carries the full burden. It implies a read-only analysis operation (explaining does not suggest mutation), and mentions outputs like tables, columns, conditions, and optimization tips. However, it does not explicitly state that the query is not executed, nor describe potential error behavior or output format details. This is adequate for a simple analysis tool but lacks explicit safety confirmation.

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 clear sentence, front-loaded with the primary action ('explain'), followed by a list of sub-features. Every word adds value, with no filler or redundancy.

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?

For a tool with one parameter and no output schema, the description is largely complete: it tells the agent what to provide (a SQL query) and what to expect (plain English explanation with structural analysis and optimization tips). Minor gaps include not specifying whether the query needs to be valid or if it supports all SQL dialects, but these are not critical for basic usage.

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?

The input schema already describes the sole parameter as 'The SQL query to explain' with 100% coverage. The description adds no additional meaning about the parameter's format, syntax, or validation. Per the rubric, baseline 3 applies when schema coverage is high, and the description does not need to add more.

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 verb 'explain' applied to a SQL query, and specifies the output: step-by-step plain English, identification of tables, columns, conditions, and optimization tips. This distinguishes it from siblings like sql_format (formatting) and query_build (constructing queries).

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?

No explicit guidance on when to use this tool vs the alternatives. It does not mention when not to use it, such as for formatting or building queries, nor any prerequisites like valid SQL syntax. The context must be inferred from the name and description.

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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