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

No annotations are provided, so the description carries the behavioral disclosure burden. It usefully discloses case-insensitive matching and the 50-row cap, but does not mention ordering, pagination, or default limit behavior. For a read-only search tool, the disclosed traits are meaningful but not exhaustive.

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?

A single, front-loaded sentence with no filler. It efficiently conveys the matching rule, case sensitivity, and result cap.

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?

For a simple two-parameter search tool with no output schema, the description adequately conveys core behavior and constraints. It could be more explicit about return format and default limit, but an agent can correctly select and invoke the tool based on the given information.

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 schema documents query as 'text to look for in any cell', and the description adds case-insensitivity. The limit parameter has no schema description, but the description's 'up to 50' indirectly aligns with its maximum. With 50% schema coverage, the description partially compensates but does not fully define limit's default behavior.

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 specific operation: return rows from the Sudslane dataset whose cells contain the query, case-insensitively, up to 50. This clearly distinguishes it from sibling tools like dataset_stats or dataset_top by focusing on content-based search.

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 the tool: when you need rows matching a substring query across cells. However, it does not explicitly mention sibling tools or conditions where an alternative would be preferable.

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