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

No annotations are provided, so the description must carry the full burden. It discloses case-insensitive matching but says nothing about read-only behavior, return format, multiple row handling, or error conditions. For a lookup tool, some behavioral context is expected.

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 sentence with no filler. It is appropriately concise and front-loaded with the essential information about the tool's function.

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 description is minimal and leaves critical gaps: no usage guidance, no parameter details, and no output specification. While the tool is simple, the lack of any guidance beyond the core action makes it incomplete for an agent to use correctly.

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%, and the description adds no explanation of the 'column' and 'value' parameters. It does not specify valid column names, value formats, or case-handling nuances beyond the single mention. The agent gains no additional meaning from the description.

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 the tool returns rows from a specific dataset where a column matches a value exactly, with case-insensitivity. This is a specific verb-resource combination that differentiates it from dataset_search, though it does not explicitly name the alternative.

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?

There is no guidance on when to use this tool versus dataset_search or other siblings. The description does not mention scenarios, limitations, or when exact match is preferred over fuzzy search.

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