get_churn_summary

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

No annotations are provided, so the description carries the full burden. It states what is computed and that churn rate is returned as a ratio between 0.0 and 1.0, but does not explicitly confirm read-only behavior or any potential performance implications. The nature of a summary tool makes this minor, but a 3 is appropriate given the lack of explicit safety disclosure.

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, front-loaded sentence that immediately states purpose and output format. No redundant words or filler.

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?

For a simple, parameter-less tool with an output schema, the description covers the key return values (counts, rate) and their format (ratio 0-1). Agents have everything needed to call it 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?

With zero parameters, the schema is trivially fully covered. The description adds no parameter-specific details because none are needed, meeting the baseline of 4 for parameter-less tools.

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?

Clearly states the verb 'calculates' and enumerates specific outputs (customer count, churned count, retained count, historical churn rate) across the entire dataset, distinguishing it from sibling get_churn_by_dimension which presumably breaks down churn by dimensions.

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?

Makes the scope explicit ('across the entire Telco dataset'), implying it is the tool for overall metrics. However, it does not explicitly contrast with alternatives like get_churn_by_dimension or mention when not to use it, so it stops short of a full 5.

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