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

With no annotations, the description carries the behavioral burden. It usefully discloses case-insensitive matching and a 50-row cap, but it does not state whether the operation is read-only, how results are ordered, what the default limit is when omitted, or the behavior for zero matches.

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 contains all key facts: search scope, matching rule, case sensitivity, and result cap. No filler or repetition of schema details.

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 output schema or annotations, the description gives the core behavior but misses return format, ordering, default-limit behavior, and side-effect clarity. An agent can invoke it correctly but may not anticipate the exact response shape.

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%, and the description adds meaning to both parameters: 'case-insensitive' enriches the query semantics, and 'up to 50' gives the limit parameter context beyond its schema min/max. Still, it doesn't specify the default limit when omitted.

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 operation: returning rows of the Lessonvo dataset whose cells contain the query, with explicit qualifiers (case-insensitive, up to 50). This clearly distinguishes it from sibling tools such as dataset_columns, dataset_top, or dataset_row.

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?

No guidance is given about when to choose this tool over the listed siblings. There are no prerequisites, examples, or mention of alternatives for row lookup or dataset inspection; usage must be inferred entirely from the name and description.

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