describe_table

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool 'return[s]' information, implying a read-only operation, but it does not describe edge cases (e.g., nonexistent table), error behavior, or the optional database context. This is adequate for a simple tool but lacks depth.

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 a single, front-loaded sentence with no filler. It efficiently communicates the core function and return fields.

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 tool is simple, and an output schema exists, so return format is covered. However, the description omits the database parameter and does not differentiate the tool from execute_query for schema exploration. This leaves some context gaps.

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 0%, so the description must explain parameters. It only mentions 'a table' implicitly referring to the table parameter, but does not describe the database parameter at all, nor does it clarify whether the table name is per database or fully qualified. This is a notable gap.

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 clearly states the tool's function: 'Return column information (name, type, null, key, default, extra) for a table.' This is a specific verb+resource combination that distinguishes it from siblings like list_databases and list_tables, which operate at a different level.

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 usage is implied by the description: you would use this tool when you need column metadata for a table. However, there is no explicit guidance on when to use it instead of alternatives like execute_query, nor any mention of the optional database parameter or prerequisites.

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