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 does reveal the ordering behavior ('in the order given') and the filtering logic, but it omits details such as whether all columns are returned, what happens with no matches, or any side effects. For a read-only query tool, this is partial but not severe.

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 that conveys the core behavior and use case with zero filler. Every clause earns its place, and the most important constraint (row filtering and ordering) appears first.

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?

The tool is simple (2 parameters, no nested objects, no output schema), so the description is mostly adequate. However, it does not state the return format, whether all columns are included, or any failure behavior. Given the simplicity and the absence of annotations, this is a minor gap but not crippling.

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 0%, so the description must compensate. It explains that 'column' is the field to filter on and 'values' are the matching values, and notes that rows follow the given value order. This adds meaning beyond the bare schema names, but it doesn't clarify data types, value format, or edge cases like empty strings, leaving some ambiguity.

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 ('compare') and resource ('rows of the Mashzo dataset'), with precise scoping: rows whose column matches any of the given values, in the order given. It also names the use case ('X vs Y questions'), which clearly distinguishes it from siblings like dataset_search or dataset_top.

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 comparison scenario, which helps an agent decide when to use it. However, it does not explicitly contrast with alternatives like dataset_search or dataset_row, nor state when not to use it. The guidance is implied rather than explicit.

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