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

Annotations already establish a safe read profile (readOnlyHint=true, destructiveHint=false), yet the description adds substantial behavior beyond them: the default 90-day trailing window, the gross 'header match including cancelled/zero-quantity orders' semantics of the asin filter, and null order_total_amount for unfinalized pending orders. This is exactly the extra 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?

Long but front-loaded and dense with non-redundant facts — scope, grain, date defaults, filter semantics, null-value caveat, and sibling routing. Each sentence carries information an agent needs; nothing restates the title or schema verbatim.

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 an 11-parameter, zero-required read tool with an output schema, the description covers what matters: grain, filter semantics, date-window defaults, null-value caveats, and tool selection. Return-value details are correctly left to the output schema.

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 3 is the baseline, but the description adds genuine meaning the schema lacks: the asin filter matches order headers that contain the ASIN (gross, not units sold), purchase_date is the seller reporting date, and the omitted-date default. It stops short of covering a few params like include_diagnostics and include_raw_rows.

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?

States a specific verb and resource ('inspect or filter channel-complete individual order headers from the Orders API') plus explicit grain ('one row per order'). It actively distinguishes itself from nearby siblings, naming get_sales_summary and product-level sales tools as the wrong choice for marketplace sales totals.

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 explicit when-not guidance ('Do not use as the primary tool for Amazon marketplace sales totals; use get_sales_summary...') and an actionable routing rule for the date window: omitting dates returns only trailing 90 days, and any historical/YoY period requires explicit start_date/end_date.

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