sample_rows

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

With no annotations, the description carries the full burden. It discloses the row limit (max 50) but does not explicitly state that the operation is read-only, safe, or how sampling is performed (e.g., random vs. arbitrary). It implies non-destructive use but does not explicitly confirm the behavioral profile.

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 two sentences, front-loaded with the core action, and every sentence adds value. No waste 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?

The tool is simple and the description covers its main purpose and constraint. However, it omits the `schema` parameter and does not explicitly confirm read-only behavior. Given an output schema exists, return-value documentation is not needed, so the description is mostly complete but has a couple of minor gaps.

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%, so the description must compensate. It explains the `limit` and `table` parameters, but the `schema` parameter is not mentioned at all. This partial compensation places it at a mid-level score.

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 tool 'Return up to `limit` sample rows from a table', using a specific verb and resource. It also differentiates from sibling tools like run_query (full query execution) and describe_table (schema inspection) by emphasizing the 'sample' aspect.

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 gives clear context on when to use the tool: 'before running real analytical queries'. It implies the alternative is to use a real query tool, but does not explicitly name alternatives or exclusion cases, so it stops short of a 5.

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