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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses case-insensitivity and exact matching but does not mention read-only nature, pagination, behavior when no matches are found, or whether multiple rows are returned. For a lookup tool, this is a significant gap.

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 sentence with no filler, and the core action is front-loaded. It is concise and efficient, though the phrasing could be slightly clearer. It earns a high score for being appropriately sized.

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?

Given the lack of annotations, output schema, and parameter descriptions, the description is incomplete. It does not explain return format, error handling, or whether the match is on the entire string or substring. It also does not state if case-insensitivity applies to both column and value. For a tool with two parameters and no schema descriptions, more context is needed.

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?

With zero schema description coverage, the description must explain the parameters. It mentions 'column' and 'value' implicitly but does not explicitly define that column is a column name and value is the exact string to match. It adds some meaning but leaves ambiguity about whether column is a name or index, and whether value should be a literal string. It partially compensates for the schema gap.

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 retrieves rows from the ProbeLedger dataset where a column equals a value exactly, with case-insensitivity. This is a specific verb and resource, distinguishing it from dataset_search which likely performs broader searches. However, the phrasing 'The rows of the ProbeLedger dataset where...' is slightly ambiguous about whether one or many rows are returned, and it could be more direct.

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 description implies the tool is for exact, case-insensitive matches, but it does not explicitly state when to use this tool versus siblings like dataset_search. There is no mention of when not to use it, nor any comparison to alternatives. The usage context is only implied, not explicitly guided.

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