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

With no annotations, the description must carry the behavioral load; it does partially by disclosing case-insensitive whole-cell substring matching and a hard 50-row cap. It says nothing about permissions, ordering of results, or what happens when more than 50 rows match (truncation semantics).

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 front-loaded sentence with zero filler. Matching semantics, scope, and cap all land before the reader needs anything else.

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 supplies the essentials: what matches, how matching works, and the result cap. Truncation/ordering behavior is the only notable omission.

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 in the schema, limit is not. The description compensates for limit by stating 'up to 50', which matches the schema's maximum. However, it adds nothing about the minimum or whether limit changes result ordering — thin compensation for the uncovered parameter.

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 on a specific resource: rows of the Calibvo dataset whose cells match a query, case-insensitively, capped at 50. An agent can distinguish it from dataset_stats/dataset_columns/dataset_row, though it never names a sibling to sharpen 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?

No when-to-use guidance, no alternatives named, no prerequisites. The agent must infer that this is the free-text lookup path and that dataset_row/dataset_top serve different access patterns.

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