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

With no annotations provided, the description carries the full burden and does disclose key behavior: case-insensitive substring matching across all cells and an output limit of 50 rows. It does not mention ordering, default limit behavior, or empty-result handling, but the core selection-relevant behaviors are explicit.

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 that contains no filler. Every word earns its place and the most important scoping information appears first.

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?

Given the low complexity of a two-parameter search tool, the description covers the required query, optional limit, match semantics, and maximum result size. The lack of an output schema and a few minor unspecified behaviors (ordering, default limit) remain, but they are not critical for selecting or invoking this 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?

The schema already documents the query parameter ('text to look for in any cell'), while the limit parameter has no schema description. The description adds 'case-insensitive' and 'up to 50' — useful context for query semantics and the result cap — but it does not clarify the limit parameter's default or behavior beyond the schema's min/max.

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 exactly what the tool does: returns rows of the Turndownly dataset whose cells contain the query, with case-insensitive matching and a 50-row cap. This is specific and clearly distinguishes it from sibling tools like dataset_stats or dataset_columns.

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 wording implies a text-search use case, but no explicit guidance is given about when to choose this over siblings like dataset_row or dataset_provenance. There are no exclusion conditions or alternative tool mentions, so an agent must infer usage from the description alone.

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