get_store_analytics

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

The description discloses the output contents (metrics returned) but does not clarify the data scope (e.g., which store, time range) or any limitations like data freshness or permissions. With no annotations provided, the description carries the full burden, but it is a read-oriented tool and the core behavior is reasonably 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 a single sentence, front-loaded with the action and resource, and every listed item adds value. No filler or redundant words.

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?

Given no output schema, the description lists the key return components (orders, revenue, products, recent activity). It is largely complete for a no-parameter analytics tool, though it leaves minor ambiguity about how the store context is determined.

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 input schema has zero parameters, so the schema coverage is trivially 100%. Baseline is 4 because there are no parameters to document; the description does not need to add parameter semantics.

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 uses the specific verb 'Get' with the resource 'store analytics', and enumerates the exact metrics returned (total orders, revenue breakdown by status, product count, recent order activity). This clearly distinguishes it from sibling tools like get_store or list_orders.

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 implies clear usage when aggregated store analytics are needed, and the specific metric list signals this tool is for summaries rather than raw data. No explicit alternatives are named, but the purpose is distinct enough that the intended context is evident.

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