get_churn

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

No annotations are provided, so the description carries the full burden, and it does disclose the output shape (percentages lost, churn counts, churned MRR). However, it says nothing about permissions, cost, or how churn is defined (e.g., cancellation window), which matters for a metric 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?

Two tight sentences with zero waste. The primary purpose is front-loaded and the return values follow immediately.

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?

With no output schema, the description usefully enumerates return metrics, and the only parameter is fully documented in the schema. Only a definition of how churn is measured and any default-period behavior caveats are missing.

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 100% and the single parameter's default, min, and max are fully documented in the schema. The description adds only 'for a given period,' which conveys no detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb ('Compute') and resources ('customer churn rate and revenue churn rate'), and enumerates the returned metrics. It is clearly distinct from get_mrr or get_subscriber_stats by name and content, though it does not explicitly name a sibling to avoid.

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 when-to-use guidance, no mention of alternatives among the seven sibling analytics tools, and no prerequisites or exclusions. The agent must infer the context from the name alone.

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