Describe a table

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

Annotations already declare read-only, idempotent, and non-destructive. The description adds crucial behavioral context: null 'description' means undocumented, not unused, preventing a common analytical error. This goes beyond the annotations to clarify interpretation of results.

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?

The description is two sentences long. The first sentence efficiently lists the returned metadata categories, and the second adds a high-value clarification about null descriptions. Every word earns its place with no redundancy.

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?

For a simple describe tool, the description covers the return contents (columns, types, nullability, defaults, PK, comments) and an important edge case (null comment semantics). Annotations handle safety, and no output schema exists, so the description fully carries the explanatory burden.

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?

Schema description coverage is only 33%, with only 'database' having a description. The tool description does not explain the semantics of 'schema' or 'table' parameters, nor does it clarify that two are required and one optional. Parameter meaning relies entirely on names, which is inadequate given the low schema coverage.

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?

Clearly specifies the tool returns column metadata (names, types, nullability, defaults, PK, comments) for one table. This distinguishes it from sibling tools like list_tables and list_schemas, which focus on listing rather than describing a single table's structure.

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 use for inspecting a table's schema but provides no explicit 'when to use' or named alternatives. It gives context about what information is returned, which hints at suitable scenarios, but lacks exclusions or comparisons to sibling tools.

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