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dann26parr69

aifordatabase-mcp

by dann26parr69

run_query

Execute SQL queries directly on a database connection. Returns columns, rows, execution time; errors include database messages.

Instructions

Run a SQL query directly against a database connection. Deterministic, no AI in the loop, no credits consumed. Returns columns, rows, rowCount, executionTime. On a SQL error the database's own message is returned — fix the SQL and retry. Rows cap at 500, so aggregate in SQL rather than pulling raw tables.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sqlYesThe SQL statement to execute
connectionIdYesConnection id from list_connections
Behavior4/5

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

Discloses determinism, no credit consumption, return format, error behavior, and row cap. Lacks mention of write safety (SQL could be INSERT/UPDATE), but overall good transparency given no annotations.

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?

Three sentences, front-loaded with purpose, no wasted words. Each sentence adds essential information.

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?

Covers purpose, usage, error handling, row cap, and return fields. Adequate for a simple 2-parameter tool without output schema.

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?

Schema coverage is 100% but parameter descriptions minimal. The description adds value by explaining how to use SQL (aggregate) and behavior, meeting the baseline for high schema coverage.

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 clearly states the tool runs a SQL query directly against a database connection. It distinguishes itself from siblings by highlighting determinism and lack of AI/credits, but does not explicitly name alternatives.

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?

Provides guidance on when to use (direct SQL, no AI), error handling (fix SQL and retry), and best practice (aggregate due to row cap). Does not explicitly state when not to use, but context with siblings implies alternatives.

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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