get_sample_data

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

With no annotations provided, the description carries the full burden. It implies a read-only preview, but does not explicitly state that it returns a limited sample (though the schema has a limit parameter), nor does it mention safety, performance, or that data is not modified. The word 'Preview' helps, but details like maximum rows and default behavior are absent.

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?

Two sentences: the first states the core function, the second explains the typical use case. No extraneous words, no redundancy. Highly 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?

The tool is simple (3 parameters, no nested objects) and has an output schema, so the description does not need to explain return values. The purpose and usage are well covered. Slight gap: it does not mention the row limit default or that it is a sampling operation, but the schema fills in the parameter details.

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?

All three parameters (limit, connection, table_name) are fully covered by the input schema with descriptions. The description adds no additional semantic meaning beyond what the schema already provides. 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 a specific action ('Preview a few rows') and resource ('a table') with an explicit purpose ('understand its data shape'). This distinguishes it from sibling tools like list_tables (metadata only), describe_table (schema), and execute_query (arbitrary queries), making its unique role obvious.

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 provides clear context for when to use: 'before generating queries' to understand actual values (statuses, date formats). It does not explicitly mention alternatives or when not to use it, but the use case is concrete and actionable.

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