get_churn_by_dimension

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

With no annotations, the description carries full responsibility for behavioral disclosure. It states the calculation output but does not mention whether the operation is read-only, how it handles invalid dimensions, whether results are sorted, or any pagination/limits. The phrase 'approved categorical dimension' hints at a validate set but does not specify behavior on unapproved input. This is insufficient for a tool with zero annotation coverage.

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 that front-loads the core action ('Calculates customer count, churned customer count, and historical churn rate') and then immediately provides examples. There is no filler or redundant wording; every clause adds value.

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 tool has only one simple parameter and an output schema exists (as indicated by context), the description covers the essential elements: what metrics are returned and what type of input is expected. The only notable gap is the lack of a complete list of approved dimensions, which the output schema may not address. Overall, it is sufficient for a straightforward analytical tool.

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?

The schema provides only a bare string parameter with no description (0% coverage). The description adds significant meaning by listing valid example values (contract, internet_service, payment_method, etc.) and clarifying that grouping is by a single approved categorical dimension. This helps the agent choose appropriate values, though it does not enumerate the full allowed set or specify where to find it, so it falls short of a 5.

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 the verb 'calculates' and the resource 'churn metrics' grouped by a categorical dimension. It lists specific output metrics (customer count, churned customer count, historical churn rate) and provides multiple concrete dimension examples, making the tool's purpose unambiguous and distinct from a general summary tool.

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 when to use the tool (when you need churn metrics grouped by a categorical dimension) by listing example dimensions, but it does not explicitly mention alternatives such as get_churn_summary for overall churn or describe_column for column analysis. It lacks an explicit when-not-to-use or comparison to siblings, leaving some routing to inference.

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