describe_table

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds value by specifying exactly what the tool returns (columns, types, keys, defaults), providing behavioral context beyond the annotations.

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 sentence that is front-loaded with the use case and contains no extraneous information. Every word earns its place.

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?

The output schema exists, so return values are already documented. The description covers the tool's purpose and parameter meaning sufficiently for a simple read-only operation. Nothing critical is missing.

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 has no description for the 'table' parameter (0% coverage). The description clarifies that it refers to a MySQL table name, which is helpful, but it doesn't specify naming conventions or whether it expects a qualified name (e.g., schema.table). Minimal but adequate for a single obvious parameter.

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 states a specific action—retrieving columns, types, keys, and defaults—for a MySQL table. It clearly distinguishes itself from sibling tools list_tables (which lists tables) and query (which runs SQL) by specifying schema inspection.

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?

It provides an explicit 'use when' condition: when you need schema details for one MySQL table. It doesn't mention alternatives or when not to use it, but the context is clear enough for an agent to select it over list_tables or query.

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