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

With no annotations, the description carries the full burden: it usefully discloses case-insensitive matching across any cell and a hard 50-row result cap. However, it says nothing about ordering, pagination, or what happens on very broad matches, so behavioral disclosure is partial.

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 with the matching semantics and result cap; every clause earns its place and nothing is redundant.

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 read-only search over two parameters with no output schema, the description covers matching semantics and result bounding adequately. It is slightly thin on result ordering and truncation behavior, but nothing critical to correct invocation is missing.

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 coverage is only 50% (the limit parameter has no description), so the description must compensate. It partly does: 'case-insensitive' enriches the query parameter beyond the schema's 'text to look for in any cell', but 'up to 50' merely restates the schema's documented maximum for limit.

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?

States a specific verb and resource: returns rows of the Insurance by Profession dataset whose cells match the query. The case-insensitive matching rule and 50-row cap make the operation unambiguous and clearly distinct from siblings like dataset_row, dataset_top, or dataset_stats.

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 when-to-use guidance and no mention of alternatives such as dataset_top or dataset_row for other retrieval patterns. The agent must infer usage from the operation itself, with no exclusions or prerequisites stated.

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