get-table-sample-data

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

No annotations are provided, and the description does not disclose behavioral traits such as whether the operation is read-only, any side effects, authorization requirements, rate limits, or output structure. This leaves the agent with insufficient information about the tool's behavior.

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, concise sentence with no unnecessary words. It front-loads the action and target, making it efficient for an agent to parse.

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 no output schema and no annotations, the description lacks details about the returned data format, row limits, or pagination. For a simple tool, it covers the basic purpose but misses important contextual information for agent usage.

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 is 100% for the single parameter 'id' with a descriptive string. The description adds context by specifying 'by UUID', but does not add significant meaning beyond the schema. Baseline of 3 is appropriate.

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 clearly states the action ('Get sample data rows'), the target resource ('a table by UUID'), and provides a usage hint ('use this instead of querying BigQuery directly'), effectively differentiating it from siblings like 'get-table-sample-data-by-name'.

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 explicitly recommends this tool over direct BigQuery queries, offering clear context for when to use it. It implicitly distinguishes from the by-name variant by specifying UUID, though it could state when not to use it more directly.

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