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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds that this is an own-account signal and that cross-merchant intelligence is not yet available, but it does not describe return shape, pagination, auth requirements, or rate limits.

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 short and front-loaded, leading with the core purpose and metrics before adding scope caveats. The stray trailing '[#f6f4f3]' artifact is minor noise that keeps it from being a clean 5.

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 four-parameter analytics tool with no parameter descriptions and no output schema, the description is too thin. It conveys the high-level purpose but leaves scope, time window, workspace/store targeting, and return structure unexplained.

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 0%, with four parameters including two enums, and the description does not explain scope, workspace, store_uuid, or time_window. It names example metrics but does not map them to any parameter or clarify valid values beyond what the bare schema already lists.

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 gives a specific verb and resource: 'Surface insights from the merchant's own products + orders', with concrete examples like best sellers, top channel, and average order value. It also clarifies own-account scope versus future cross-merchant intelligence, though it does not explicitly differentiate from the many analytics_* siblings.

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 an analytics use case but does not state when to use this tool instead of alternatives such as analytics_summary, analytics_breakdown, channel_performance, or analytics_ops. It notes own-account scope and read-only behavior, but offers no explicit when/when-not guidance.

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