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

No annotations are provided, so the description carries the full behavioral burden. It does disclose one genuinely useful trait — result rows follow the order of the supplied values, which is a real semantic contract. It says nothing about read-only nature, permissions, or what a returned row contains, leaving gaps for a zero-annotation tool.

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 tight sentence with no padding; the filter rule leads and the use case trails, so the most important information is front-loaded.

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 2-parameter tool with no output schema and no annotations, the description covers the filter and ordering contract adequately. It is silent on value-count limits and on what the returned rows/columns look like, which is left entirely to inference.

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 compensate, and it does explain the two parameters meaningfully: 'column' is the matched field, 'values' is treated as an any-of membership set, and output order follows 'values' order. It omits the schema's minItems=2/maxItems=10 constraints, which a caller could otherwise violate.

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 identifies the resource (rows of the FlightDelayHQ dataset) and the exact selection rule (column matching any of the given values, output in input order), so an agent knows it is a filtered row retrieval rather than an aggregate. It stops short of a clear verb ('returns'/'selects') and never names a sibling to contrast with dataset_search or dataset_row.

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 closing clause 'for "X vs Y" questions' gives a concrete scenario for choosing this tool. It offers no when-not guidance and does not point to dataset_search or dataset_row as alternatives when the caller only needs a single match or a full-text lookup.

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