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

No annotations are provided, so the description carries the burden. It discloses case-insensitive matching, the row-based return scope, and the 50-row cap, which is useful behavior. However, it does not mention what happens when the query matches no rows, whether pagination is supported, or any performance implications.

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?

One sentence, front-loaded with the action and scope, and includes the key constraint (case-insensitive, up to 50). 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?

Given 2 parameters and no output schema, the description covers the core behavior but misses details like default limit behavior, empty result handling, and sorting. It is adequate for a simple search tool but leaves some practical questions unanswered.

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%; the 'query' parameter is documented in schema as 'text to look for in any cell', and the description adds the case-insensitive and row-context detail. The 'limit' parameter is not described in the schema, and the description only implies a cap of 50, not how the limit parameter behaves or its interaction with the cap. This is a partial 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 clearly states the verb 'search' and the resource (Clientvo dataset rows), and specifies the case-insensitive matching behavior. However, it does not explicitly differentiate from sibling tools beyond the scope of this dataset, though the name 'dataset_search' helps.

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 usage: search within a dataset when you need rows matching a query. It does not explicitly state when to use alternatives like dataset_columns or dataset_stats, nor any exclusions. The 'up to 50' limit provides some context but not explicit usage guidance.

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