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 real traits: matching is case-insensitive substring-anywhere, results are capped at 50 rows, and the scope is fixed to one named dataset. It omits ordering, whether the limit is silently applied or assumed, and what happens on no matches, so it is partially transparent but not complete.

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 resource and match condition, ending with the size constraint. No filler words and nothing redundant with the tool name.

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?

There is no output schema and no annotations, so the description is the only source of behavior. It conveys the shape of results loosely ('rows ... up to 50') but says nothing about returned fields, ordering, or behavior with an empty result set. Adequate to invoke, thin for interpreting the response.

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 50%: 'query' is documented as 'text to look for in any cell' while 'limit' carries only bounds with no description. The description partially compensates by restating the 50-row ceiling, which maps to the limit maximum, but it never explains that limit controls result count. Baseline 3 is appropriate given the schema does roughly half the work.

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/rows matched by content) tied to a named resource and scope: 'Rows of the Wedding Cost Checker dataset whose cells contain the query'. It also states the matching semantics (case-insensitive, any cell) and the cap (up to 50), so an agent knows this is a full-text scan rather than a field lookup. However, it never distinguishes itself from siblings like dataset_row, dataset_top, or dataset_compare, so the agent must infer the boundary.

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 statement, no when-not, and no mention of the sibling alternatives (dataset_row for a single record, dataset_top for ranked results, dataset_columns for schema). Usage is only implicitly derivable from the phrasing 'cells contain the query'. An agent must guess which of the six dataset_* tools is appropriate.

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