Subscription and customer churn

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

Annotations already state readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered and the bar is lower. The description adds genuinely useful behavioral detail (cohort definition, window boundary, null-rate case, currency segmentation), but omits the scale of the rate: e.g., whether it is a fraction or a percentage, which matters because there is no output schema.

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?

It is a single, front-loaded sentence with no filler: the metric, the cohort, the window, the edge case, and the currency breakdown all earn their place. The dense parentheticals make it slightly harder to parse than necessary.

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?

This is a simple one-parameter read tool with no output schema, and the description covers the cohort definition, the edge case, and the return segmentation. The only real gap is the rate's units/scale, which an agent would need in order to present the result 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 100% and the days parameter is fully documented (1-365, default 30). The description repeats 'last N days' and clarifies that the window ends at the close, which adds some cohort semantics but no new syntax or constraint information. Baseline 3.

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 metric (churn) computed over a defined cohort and window, plus what is returned: subscription and customer churn rates and churned MRR per currency. This is clearly distinct from the sibling tools get_mrr, revenue_summary, and list_failed_payments, which address different analytical questions.

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?

Usage is implied by the metric itself, but the description never says when to reach for this rather than get_mrr or revenue_summary, nor does it give any exclusions or prerequisites. The agent must infer the routing decision from the tool names.

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