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

The description discloses case-insensitivity and the 50-row limit, but does not mention sorting, pagination, behavior with no results, or whether all columns are searched. There are no annotations to contradict, so the disclosed behavior is not misleading, but important edge cases are omitted.

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, efficient sentence that conveys the essential search behavior, scope, and limit without extraneous detail. It is well-structured and immediately understandable.

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?

While the description is clear for a simple search, it lacks contextual information such as return format, potential error conditions, or relationship to sibling tools. Given the simplicity of the operation, the missing details are notable but not critical.

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 provides a description for 'query' ('text to look for in any cell'), but 'limit' has no description in the schema. The description partially covers 'limit' by mentioning 'up to 50', but the parameter's exact semantics (e.g., default value, bounds) are not fully specified.

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 searches rows of the 'KnownVehicle' dataset for a query in any cell with case-insensitivity, and specifies a limit of 50 results. This fully identifies the tool's purpose and differentiates it from other dataset operations.

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 no guidance on when to use this tool versus alternatives like dataset_row, dataset_columns, or dataset_stats. There is no mention of scenarios where search is preferred or how it fits into a larger workflow.

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