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

There are no annotations, so the description carries the full burden. It mentions case-insensitive matching and a row limit, but doesn't state whether the operation is read-only, whether it has side effects, or what the return format is. The read-only nature is implied but not explicitly disclosed.

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, clear sentence that conveys the essential behavior without superfluous words. It's well-structured and directly addresses what the tool does.

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 description is sufficient to understand the core function and constraints (case-insensitive, up to 50 rows). It lacks details on output structure or error handling, but for a simple search tool, it provides enough context for basic usage.

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 covers both parameters, but only 'query' has a description. The description of 'query' adds minimal value beyond the schema (just reiterates it's text to search). 'limit' has no description, and its semantics are only implied by its name and min/max. Overall, the description adds little to the schema.

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 that the tool searches for rows containing the query across all cells, is case-insensitive, and returns up to 50 rows. While it doesn't explicitly differentiate from sibling tools like dataset_columns or dataset_stats, the purpose is specific and unambiguous.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, typical use cases, or situations where a sibling tool might be more appropriate.

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