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joyous-coder

universal-db-mcp

by joyous-coder

lint_sql

Identify errors, warnings, and info in SQL queries. Returns an advisory issues list to help improve query quality without blocking execution.

Instructions

Lint a SQL query. Returns issues array (error/warning/info). Advisory, never blocks.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv5.0.2

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full disclosure burden. It does state the tool is 'Advisory, never blocks,' disclosing that it is non-blocking and safe, and it specifies the return shape as an issues array. It does not go into further detail about whether it uses a database connection or a specific SQL dialect, but the core behavioral traits are covered.

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?

Two sentences, no filler, and the key action is front-loaded. Every word earns its place.

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 single-parameter, no-output-schema tool, the description covers the essential contract: what input it takes, what it returns, and how it behaves (advisory, non-blocking). It doesn't detail the issue object structure or prerequisites like an active profile, but given the low complexity, the description is sufficiently complete.

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

Parameters4/5

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

The schema has zero description coverage, and the description must compensate. It mentions 'a SQL query,' directly mapping to the single 'sql' parameter. While it adds no format constraints or dialect details, the parameter's purpose is clearly conveyed by both its name and the description.

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 opens with a specific verb and resource: 'Lint a SQL query.' It immediately states what the tool operates on and clarifies the output as an issues array with severity levels. This clearly distinguishes it from sibling tools like execute_query or explain_query, which have different purposes.

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 description says 'Advisory, never blocks,' implying the tool is for safe, non-executing checks and giving some context on when to use it. However, it does not explicitly name alternatives such as explain_query or execute_query, nor does it state when not to use it. The usage guidance is implied rather than explicit.

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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