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

With no annotations, the description carries the full burden of behavioral disclosure. It only reveals that matching is case-insensitive and exact, but does not mention the return format, behavior on zero matches, potential multiple matches, or any error conditions. For a read-only lookup, this is a significant gap—agents cannot predict what the response will look like or whether it might be empty.

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?

The description is a single, front-loaded sentence that conveys the core purpose immediately. There is no extraneous information, and the key qualifier ('exactly', 'case-insensitive') is placed prominently. It is efficient and to the point.

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?

Given the tool's simplicity (2 string params, no output schema), the description is reasonably adequate. It covers the matching logic but omits details about the return shape (list vs. single row), pagination, or handling of no matches. Since there is no output schema to fill this gap, the description should have provided at least a hint about what the response contains. This is a noticeable, though not critical, omission for such a straightforward lookup 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 0%, so the description must explain the parameters. It does so indirectly: 'a column' maps to the 'column' parameter and 'a value' maps to the 'value' parameter, clarifying their roles in the query. However, it does not provide examples, format constraints, or edge cases, so it only partially compensates for the lack of schema documentation.

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 action ('look up a row') on a specific resource ('Tenantvo dataset') with a precise condition ('where a column equals a value exactly, case-insensitive'). It clearly differentiates from siblings like dataset_search (which implies broader search) and dataset_top (which implies ranking), making the tool's purpose unambiguous.

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 implies when to use this tool (when an exact, case-insensitive match is needed) but provides no explicit guidance on when not to use it or which sibling to choose instead. It lacks direct comparisons to dataset_search or other alternatives, leaving the agent to infer based on the phrase 'exactly'.

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