Shopify Weekly Financial Summary

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive). The description adds genuinely useful behavior beyond that: it fetches ALL orders in the period and auto-paginates, which warns the agent that this is a heavy, full-scan read rather than a bounded query. It stops short of 5 by not noting rate limits, cost, or result size.

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 with the aggregation purpose first and the computed outputs after. No filler, no restatement of the title or parameter list.

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?

No output schema exists, so the description appropriately enumerates the return metrics (revenue totals, AOV, items per order, product breakdown), which is the key missing structured information. It is slightly incomplete in that it never addresses the naming mismatch between 'weekly' and the caller-supplied arbitrary date range, nor how status_filter interacts with the aggregates.

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 date_from, date_to, and status_filter are already documented in the schema. The description only implies date-range and status scoping ('in the period', 'sorted by revenue') without adding format or filtering semantics beyond the schema. Baseline 3 applies.

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 verb set (fetches, calculates) and resource (orders/financial summary) and enumerates the computed metrics (revenue totals, AOV, items per order, product breakdown), which separates it from raw-listing siblings like shopify_list_orders. It does not explicitly name the alternative it is not, so it stops short of a 5.

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?

There is no when-to-use or when-not-to-use guidance. With siblings such as shopify_list_orders, shopify_order_count, and shopify_analytics_query in the same namespace, the agent gets no signal about when this aggregation is preferable to a raw order list or a general analytics query.

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