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

With no annotations provided, the description carries the burden of behavioral disclosure. It usefully reveals case-insensitive matching, substring containment across cells, and a 50-result cap, but it does not mention default limit behavior, sorting, empty-result behavior, or return structure.

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, well-structured sentence delivers the core behavior, matching mode, case sensitivity, and result cap without redundancy. Every phrase earns its place.

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 covers the essential invocation semantics: what is searched, how matching works, and the result ceiling. It could be more complete by stating the default limit and response shape, but the core contract is clear enough for an agent to call the tool correctly.

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 but not limit; the description adds meaningful semantics by explaining that the query is matched against cells case-insensitively and that results are capped at 50. This partially compensates for the 50% schema description coverage, though the explicit link to the limit parameter is implicit.

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 returns dataset rows matching a query, with case-insensitive cell containment and a 50-row cap. It is specific about the resource and behavior, though it does not explicitly distinguish itself from sibling tools like dataset_row or dataset_top.

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?

There is no explicit guidance about when to use this tool versus alternatives such as dataset_stats, dataset_row, or dataset_top. The intended usage is only implied by the word 'search' in the name and the contains-query semantics in the description.

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