Run a read-only SQL query

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

With no annotations, the description carries full burden. It discloses critical behaviors: read-only enforcement, result capping, and default JSON output. However, it omits details on error handling, pagination, or authentication requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, well-structured sentence conveys the tool's action, constraints, and output. Every word adds value; no redundancy or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (2 parameters, no output schema), the description provides essential context: read-only, results capped, output format options. It could mention result structure (array of row objects) or error responses, but is mostly complete.

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

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

The input schema covers both parameters (sql, format) with descriptions. The description adds value beyond the schema by specifying 'single' statement, 'read-only', and 'capped results'. This clarifies constraints not in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the verb (runs), resource (SQL query), and constraints (read-only, SELECT/WITH, capped results). It clearly distinguishes the tool's purpose from sibling tools, which are more specific (e.g., count_rows, describe_table).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

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

The description implies appropriate use cases (arbitrary read-only queries) but does not explicitly contrast with sibling tools or provide when-not-to-use guidance. For a general query tool, this is adequate but not outstanding.

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