get_table_data

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

No annotations are provided, so the description carries the full behavioral burden. It does not explicitly state that the operation is read-only, what 'sample' means (e.g., arbitrary rows vs. first N), or how results are returned. 'Get' implies a read, but side effects and output behavior are left to inference.

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 that front-loads the core purpose and then states the optional capabilities. There is no filler or repetition.

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?

Parameter-level guidance is fully provided by the schema, making invocation straightforward. However, there is no output schema and the description does not describe the return shape, nor does it position this tool against similar data-access siblings, leaving some context incomplete.

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 covers all six parameters with detailed descriptions, including defaults and a pagination caveat for offset. The tool description only summarizes 'filtering and limiting' and adds no additional meaning beyond the schema, so the baseline score of 3 applies.

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 identifies the resource ('a table') and the operation ('Get sample data'), and adds the scope ('optional filtering and limiting'). It is distinguishable from siblings like describe_table and list_tables, but does not explicitly call out how it differs from execute_query or export_table_csv.

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 'sample data' implies this is for lightweight table exploration, but there is no explicit when-to-use guidance or mention of alternatives such as execute_query or export_table_csv. Usage context is only implied, not stated.

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