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

With no annotations provided, the description carries the transparency burden. It discloses two important behaviors: case-insensitive matching and a result cap of 50 rows. This goes beyond a bare 'search dataset' statement, though it does not mention sorting, default limit behavior, or empty-result handling.

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, information-dense sentence with no fluff. It front-loads the core result type ('Rows of the Eposvo dataset') and packs in matching semantics, case sensitivity, and result limit without wasted words.

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, the description is largely complete: it specifies what is searched, how matching works, and the maximum result count. There is no output schema, but the description's promise of 'rows' is sufficient for basic invocation; minor gaps like exact row shape and ordering are not critical for selecting or calling the tool.

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 50%: only 'query' is described. The description adds useful meaning by clarifying that query matches substrings case-insensitively across cells and that results are capped at 50, which aligns with the limit parameter. However, it does not explicitly explain the limit parameter's role or default behavior, so it only partially compensates for the schema gap.

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 action: returning dataset rows whose cells contain the query, with specific behavioral details (case-insensitive, up to 50 rows). This distinguishes it from siblings like dataset_stats or dataset_provenance by focusing on content-based row 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 implies when to use the tool: when an agent needs to find rows matching arbitrary text in any cell. However, it does not explicitly state when not to use it or mention any alternative sibling tools, leaving the routing decision mostly to inference.

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