get_sample_data

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

No annotations provided, so description carries full burden. Discloses limit clamping to [1,1000], which is a key behavioral trait. Does not mention potential errors or that the operation is read-only, though that is implied. Adding a note about ordering or error handling would increase transparency.

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?

Short and to the point, using a structured Args format. Every sentence adds value. Minor reduction because the Args block is somewhat verbose for a simple tool, but overall efficient.

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 tool's simplicity and presence of output schema, description covers essential aspects: purpose, parameters, limit clamping. Lacks mention of result ordering (e.g., arbitrary) or error handling for missing tables. Still adequate for most use cases.

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 coverage 0%, so description must compensate. Adds meaning to all three parameters: explains 'database' and 'table' as plain identifiers, and documents limit clamping behavior. However, does not define 'plain identifier' (e.g., case sensitivity), so slight gap remains.

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?

Clearly states it returns the first N rows of a table, which is a specific verb+resource. Differentiates from sibling tools like query (arbitrary SQL) and describe_table (schema retrieval) by specifying a limited preview.

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?

Indirectly implies use for quick sampling ('first N rows'), but does not explicitly state when not to use it (e.g., for full queries use query) or provide alternatives. Could be improved by mentioning that query supports arbitrary SQL.

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