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

The annotations already declare this is a read-only, non-destructive, open-world tool, lowering the disclosure burden. The description adds useful behavioral context by noting the one-year lookback for new vs returning customers and that customer names are shortened for privacy, but it does not discuss limitations, permissions, or return format.

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 concise sentence that front-loads the key metrics and includes the privacy note without waste. Every clause contributes useful information.

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 read-only analytics tool with rich annotations and fully documented parameters, the description adequately enumerates the data returned. It does not specify output shape or limits such as how many top customers are returned, but no output schema exists and the core purpose is clear.

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%, so the store and period parameters are already fully documented in the schema. The description reinforces that results are for a period but adds no parameter-specific syntax or constraints beyond the schema.

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 names a specific analytics resource and enumerates the customer metrics returned: counts, new vs returning, repeat-buyer rate, and top spenders. It is clear what the tool does, but it does not distinguish itself from siblings such as customer_segments or get_sales_summary.

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 gives no explicit guidance on when to use this tool versus alternatives, nor any exclusions. Usage is only implied by the metric names, which is weak given overlapping sibling tools such as customer_segments and get_sales_summary.

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