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

With no annotations, the description carries the behavioral disclosure burden. It usefully discloses case-insensitive matching, substring containment semantics, and a maximum of 50 results. However, it does not mention ordering, pagination, empty-result behavior, or whether the query must match whole cells versus substrings beyond the word 'contain.'

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 compact sentence conveys the core behavior, the matching rule, and the result cap with no filler. The most important detail—what the tool returns—is front-loaded.

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 two-parameter search tool with no output schema and no annotations, the description is largely complete: it names the dataset, defines the query semantics, and states the result limit. It could add return-format or ordering details, but nothing essential is missing for invoking 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%: only 'query' has a schema description. The tool description adds meaning by explaining that the query is matched case-insensitively in any cell, and the 'up to 50' phrase hints at the limit parameter's cap. However, it does not explicitly state that 'limit' controls the number of returned rows, leaving some inference needed.

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 states a specific operation: returning rows of the Soapvo dataset whose cells contain the query, with case-insensitive matching and a 50-row cap. This clearly distinguishes search from the sibling tools like dataset_columns, dataset_row, and dataset_stats, which have different purposes.

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 does not say when to use this tool versus the sibling tools, nor does it mention any exclusions or prerequisites. An agent must infer that this is for cell-level substring search rather than, say, fetching a specific row or computing statistics.

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