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

Beyond the readOnly/openWorld annotations, it discloses the data provenance (order-item-sourced), the channel exclusion rule (Non-Amazon/MCF excluded so numbers reconcile with get_sales_summary), and the grain default behavior. These are meaningful behavioral traits an agent could not infer from annotations.

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?

Dense but front-loaded: purpose first, then data semantics, then grain behavior, then explicit exclusions and alternatives. Every sentence earns its place and none restate the name or title.

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-param, output-schema-backed analytical tool, the description supplies the reconciling context (source, channel exclusions, grain defaults) and routing alternatives an agent needs. Nothing critical is missing given the output schema already covers return structure.

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 the baseline is 3. The description reinforces the time_grain default and the net_units_sold vs units_ordered distinction, but these are already documented in the schema's sort_by and time_grain descriptions, so it adds little beyond what structured fields provide.

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+resource ('historical Amazon-marketplace product sales velocity and inventory planning') and defines the exact return grain ('net_units_sold by ASIN/period from Orders API data plus Business Reports'). It clearly distinguishes itself from get_orders, get_todays_sales, and get_sales_summary within the crowded sibling set.

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?

Explicit when-to-use (historical velocity, inventory planning), when-not (not current-day or account-level totals), and names the exact alternatives (get_todays_sales, get_sales_summary). It also warns against the tempting misuse of get_orders header counts as units sold and explains why.

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