shopify_orders_list

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

Goes well beyond the readOnly/idempotent annotations by disclosing a critical data-visibility boundary: only the last 60 days are visible unless the app holds read_all_orders, and older orders are silently absent. The explicit warning not to interpret an empty result as an empty history is exactly the kind of failure-mode context annotations cannot convey.

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?

Three sentences, front-loaded with the purpose, then a usage example, then the visibility caveat. Every sentence earns its place and the most important constraint (silent 60-day truncation) is placed prominently.

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?

With no output schema, the description covers purpose, filtering usage, and the key visibility caveat well enough to call the tool correctly. It stops short of describing the returned order fields or pagination flow, but paging is documented in the schema and return shape is a minor gap for a list endpoint.

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 coverage is 100% and the schema's `query` field already documents qualifiers, the typo-ignored behavior, and the created_at caveat in detail. The description's example largely duplicates the schema's own example, so it adds only marginal meaning over the structured field. Baseline 3 is appropriate.

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?

Starts with a specific verb+resource ('List orders'), which cleanly separates it from the singular shopify_order_get sibling. The rest of the description elaborates filtering rather than the core purpose, so the differentiation is implicit in the name rather than stated.

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?

Gives a concrete usage pattern with a worked search example ('financial_status:paid fulfillment_status:unshipped to find orders waiting to ship'), which tells an agent how and when to apply filtering. It does not name alternatives or state when-not to use this versus shopify_order_get, so it stops short of full routing guidance.

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