get_table

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

With no annotations provided, the description carries the behavioral disclosure burden. It transparently states the tool's read-only inspection nature and enumerates the returned information (columns, row count, sample rows). It does not discuss error cases or prerequisites, but for a simple inspection tool this is adequate.

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 or repetition. Every word contributes to explaining the tool's purpose and output.

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, has an output schema, and the description covers the core behavior and return contents. It does not explain prerequisites or edge cases, but the presence of an output schema and the low complexity make the description sufficiently complete.

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 compensate for parameter meaning. It indirectly maps to the parameters: 'one result table' implies the `name` parameter, and 'a small sample of rows' implies `sample`. However, it does not explicitly name or explain either parameter, leaving some ambiguity.

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 ('Inspect') and resource ('one result table') and clearly enumerates what is returned: columns, row count, and a sample of rows. This distinguishes it from siblings like list_tables (listing all tables) and query_table (running queries).

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 phrase 'Inspect one result table' clearly conveys when to use this tool: when you need details about a single table rather than listing or querying tables. It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to differentiate it from sibling tools.

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