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

With no annotations provided, the description carries the full burden. It discloses useful behavior: matching is based on 'any of' the given values, and results appear 'in the order given.' However, it does not describe exact-match semantics, case sensitivity, response format, or whether the operation is read-only, leaving some ambiguity.

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 efficient sentence with no filler. The primary filtering behavior is front-loaded, and the use-case note 'for X vs Y questions' is compact yet informative.

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 simple two-parameter comparison tool, the description is reasonably close to adequate. However, the absence of annotations, output schema, and any mention of return format or edge cases like missing values or duplicates leaves noticeable gaps for an agent deciding how to use the result.

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 needs to compensate for the missing parameter documentation. It adds the key relationship that the column is matched against any of the values and that order matters, but it does not clarify valid column names, value matching rules, or handling of empty results.

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 clearly states that the tool returns rows from the Abutly dataset where the specified column matches any of the given values, and that the order of values is preserved. This is specific enough to distinguish it from generic search or stats tools, though it does not explicitly reference sibling tools to differentiate them.

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' gives some usage context, suggesting the tool is meant for comparing specific rows side by side. However, it does not explicitly mention alternatives like dataset_row or dataset_search, nor does it state when not to use this tool.

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