describe_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 of behavioral disclosure. While the description implies a read-only operation (showing structure), it does not explicitly state that it is non-destructive, safe to call, or what the performance implications are. This is adequate but lacks explicit safety cues.

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, tightly worded sentence with no waste. It immediately conveys the tool's purpose without extraneous details, making it easy for an agent to scan and understand.

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 lack of an output schema, the description does not specify the format or depth of the returned structure (e.g., constraints, nullability, default values). It mentions 'columns, types, indexes' which is sufficient for basic use, but could be more comprehensive for a tool that inspects table metadata.

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 100% description coverage, so the schema already documents all three parameters. The description adds no additional meaning about parameters (e.g., default values, valid formats). The baseline score of 3 is appropriate as the description does not compensate for any schema gaps.

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 'Show table structure: columns, types, indexes' clearly states the tool's purpose with a specific verb ('Show') and resource ('table structure'). It distinguishes itself from sibling tools like 'list_tables' (which returns names only) and 'explain_query' (which explains query plans), making the function unambiguous.

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 provides no guidance on when to use this tool versus alternatives. It does not mention that it is suitable for inspecting a table before querying, nor does it exclude cases where more detailed schema documentation is needed. Without such context, an AI agent might misuse or overlook it.

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