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

With no annotations, the description carries the full behavioral burden. It does disclose the case-insensitive substring-match semantics and the 50-row cap, which are genuinely useful, but it omits return shape, ordering, default limit behavior, and any permission/read-access context.

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 tight sentence with the resource and matching scope front-loaded. No filler and nothing 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 two-parameter read tool with no output schema and no annotations, the description covers what is searched and the result cap but leaves ordering, default limit, and return field structure unstated. Adequate but not fully complete.

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 schema description), yet the description clarifies the matching semantics ('cells contain the query', case-insensitive) and restates the effective result cap of 50, adding meaning beyond the schema for the query parameter. It still does not explain the limit parameter name or its default.

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 gives a specific verb (search) and resource (rows of the Sauna Cold Plunge Compare dataset), plus the matching rule (case-insensitive, any cell) and result cap (up to 50). It is clear what the tool does, though it does not name or contrast with the 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 guidance on when to use this versus dataset_row, dataset_top, or dataset_compare. Usage is only implied by the verb 'search', and no exclusions or prerequisites are stated.

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