sample_data

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

There are no annotations, so the description carries the full burden of behavioral disclosure. It only says rows are sampled and does not explain whether the operation is read-only, how random selection works, whether filters apply via the where parameter, or what output structure is returned. This is insufficient for a tool with no annotation coverage.

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 very short, but this is under-specification rather than effective conciseness. A single phrase conveys the basic purpose but omits the parameter behavior and selection semantics that an agent needs to invoke the tool correctly.

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 five parameters, one required field, an enum, and no annotations, the description is not complete enough. It does not explain the meaning of the sampling methods, the filter syntax, or how stratify_column relates to method, so an agent cannot reliably construct a correct call from the provided text.

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%, and the description does not compensate by explaining any of the five parameters. It does not mention n, where, method, stratify_column, or table_name, leaving the agent to guess their meaning and interactions solely from names and defaults.

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 states a clear verb-resource relationship: 'sampling rows from a table.' It identifies what the tool does at a basic level, though it does not differentiate it from sibling tools like sql_query or profile_data and does not clarify whether this is a preview or statistical sampling operation.

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?

No guidance is given about when to use sample_data versus alternatives such as sql_query, profile_data, or get_schema. There is no mention of typical use cases, prerequisites, or exclusions, so an agent must infer when this tool is appropriate.

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