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

With no annotations, the description must disclose behavioral traits itself. It states that rows are returned 'in the order given' (the order of the values list), which is a key behavior. However, it does not mention whether this is a read-only operation, what happens when no rows match, whether it returns full rows or a subset, or any limits on the dataset size. It adds some value beyond the schema but lacks depth.

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, tightly worded sentence that front-loads the core functionality and includes the ordering behavior and usage hint. There is no redundancy or filler; every word earns its place.

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 tool with no annotations and no output schema, the description should fully specify what the agent needs. It explains the input semantics and the ordering, but does not describe the return structure (e.g., full rows, columns included) or edge cases like empty results. It is adequate for a simple filtering tool but leaves room for ambiguity about the output format.

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 schema only provides types and constraints. The description adds meaning by explaining that 'column' is the field used to filter and 'values' are the values to match, and that the output respects the order of values. It does not clarify details like exact match semantics, case sensitivity, or whether column must be a valid column name, but it gives the core filtering logic that the schema omits.

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 verb and resource ('rows of the Huddlevo dataset') and clarifies the filtering mechanism (column matches given values) and ordering. It includes a purpose hint ('for X vs Y questions') that distinguishes it from general search, but does not explicitly name alternatives among siblings.

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 phrase 'for X vs Y questions' implies a usage context for comparisons, but there is no explicit guidance on when to use this tool versus dataset_search, dataset_row, or dataset_top. No exclusions or alternatives are mentioned, leaving the agent to infer the appropriate scenario.

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