Describe a table

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

No annotations are provided, so the description carries the full burden. It discloses the tool's output (columns, types, nullability, defaults), which is the core behavior. However, it does not mention error handling, permissions, or what happens if the table does not exist, leaving some gaps.

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 sentence of nine words, front-loaded with the verb and resource. Every word earns its place, making it extremely concise without losing clarity.

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 operation with only two parameters and no output schema, the description provides the essential information about the return value. It does not specify output format or edge cases, but the tool's simplicity means this is minimally sufficient.

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 100% of the parameters with descriptions, so the baseline is 3. The description does not add any extra parameter-specific semantics, but the schema already defines the table and schema parameters adequately.

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 uses a specific verb 'Return' and identifies the resource as a table, listing the exact metadata fields (columns, types, nullability, defaults). This clearly differentiates it from siblings like query or list_tables, which have different purposes.

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 the tool is used to retrieve table structure, which is an implied usage context. However, it does not explicitly state when to use it versus alternatives like list_tables or analyze_query, nor does it provide exclusions or prerequisites.

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