sample_rows

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

No annotations are provided, so the description carries full burden. It discloses a 50-row cap but does not explain whether rows are random, first N, or otherwise ordered, or whether there are any side effects or permissions. For a data-fetching operation, the sampling behavior is crucial for accurate expectations.

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, front-loaded sentence that states the action, object, and a key constraint. Every word earns its place and there is no redundancy.

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 shape is covered. However, the lack of parameter explanations and sampling behavior leaves minor gaps, and there is no usage differentiation from siblings. Still, an agent could likely call it correctly for a basic preview task.

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. It adds meaning for 'table' and implicitly for 'limit' via 'up to 50', but does not mention the 'schema' parameter or explain the relationship between 'limit' and its default value. The description does not fully cover the parameter set.

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 ('Fetch') and resource ('sample rows from a table'), and clearly conveys that it retrieves table data rather than metadata, distinguishing it from siblings like list_tables and table_stats. The 'up to 50' constraint adds important scope information.

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 a clear context: use when you need a quick preview of actual rows from a table. It does not explicitly mention when not to use it or name alternatives, but the niche is evident from the tool name and description.

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