revenue_summary

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

With no annotations, the description carries the burden of explaining behavior. It discloses that it returns aggregate metrics, applies revenue filtering by `after` with a default, and distinguishes lifetime sales counts from date-filtered revenue. It does not cover error handling or auth, but for a simple read-oriented summary tool the core behavior is transparent.

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 two sentences, front-loaded with the tool's purpose, and every clause adds specific information. The only minor flourish is 'The number an operator actually wants first', which reinforces usage context without bloating the text.

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 tool with one optional parameter and an output schema present, the description fully covers what the tool does, the key metrics, and the parameter's format/default. It is complete enough for an agent to select and invoke appropriately without further clarification.

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 only defines `after` as a string with an empty default, providing 0% coverage. The description compensates by specifying the YYYY-MM-DD format and the default of 'start of current month', adding meaningful semantics that allow correct invocation.

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 clearly defines the tool as a one-call store health check, enumerating the exact metrics returned (product count, published count, lifetime sales counts per product, revenue since a date). It stands apart from siblings list_products and sales by providing an aggregated summary rather than raw lists or separate sales data.

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 phrase 'One-call store health check' and 'The number an operator actually wants first' imply this is a quick aggregate alternative to calling multiple tools, but it does not explicitly name sibling tools or state when not to use it. The guidance is clear in context but lacks direct exclusions or alternative references.

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