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

With no annotations, the description carries the burden and does disclose useful traits: matching is case-insensitive and the result is limited to 50 rows. However, it does not state whether the operation is read-only, what the output format is, or how results are ordered, leaving part of the behavior implicit.

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 conveys operation, scope, matching semantics, and cap with no filler or repetition.

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 search tool with no annotations or output schema, the description covers the core behavior, matching condition, and result cap. It does not specify output shape or ordering, but this is modest for a simple search tool.

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 only 50%; the description compensates partially by clarifying that 'query' is matched against any cell and that results are capped at 50, which also clarifies the 'limit' parameter. It does not add detail such as the default limit or the exact meaning of 'rows.'

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 the operation implicitly: it returns rows whose cells contain the query in the Reputzo dataset. It is specific about matching behavior (case-insensitive) and a 50-row cap, which distinguishes it from siblings like dataset_row or dataset_top, though it does not name a sibling explicitly.

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 or mention of alternatives. The description only defines what the tool does; an agent must infer that it should be used for text-based search, rather than for retrieving rows by ID or computing stats.

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