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 reveals key behavior: case-insensitive matching, matching across any cell, and a maximum of 50 rows. It omits pagination/ordering details, but these are minor for a simple read-oriented search.

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 sentence with no filler; the core behavior, case-insensitivity, and row limit are all front-loaded. Every word 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 search tool with two parameters and no output schema, the description is largely complete: it states the search scope, matching semantics, and result cap. It could mention ordering or the default limit, but an agent has enough to invoke 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?

Schema description coverage is 50%: query is described but limit is not. The tool description adds the case-insensitive and any-cell semantics for the query and the 'up to 50' cap, which gives context to the limit parameter. However, it does not clarify default behavior when limit is omitted.

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 identifies the operation: returning rows of the dataset whose cells contain the query, with explicit case-insensitivity and a 50-row cap. It is distinct from sibling tools like dataset_row or dataset_top, though it does not name them as alternatives.

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 this is the go-to tool for free-text search across all cells, and the sibling names suggest other specialized operations, but there is no explicit statement of when to use this tool versus alternatives or any exclusions.

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