product_fee_previewAmazon's own estimated fees per SKU for the coming weeks (referral, fulfillment, storage).
| Name | Required | Description | Default |
|---|---|---|---|
| sku | No | ||
| asin | No | ||
| seller_connection_id | No | Which seller connection (see account_sellers). Optional when the token has exactly one. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover the read-only, non-destructive safety profile. The description adds useful context by clarifying that fees are Amazon's own estimates and forward-looking, but it does not discuss response format, how the optional parameters interact, or any other runtime behavior.
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 one well-structured sentence with all terms earning their place, and the core scope ('per SKU') is front-loaded. It is easy to scan.
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?
Despite having only three optional parameters, the low schema coverage and absence of an output schema mean the description needs to explain parameter usage and what the preview includes; it only mentions fee categories and the per-SKU scope. An agent would still be guessing about required identifiers and response 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 only 33%, and the description only weakly supports the 'sku' parameter via 'per SKU'; it does not explain the 'asin' parameter or the relationship/alternation between sku and asin. seller_connection_id is already documented in the schema, so the description adds little beyond that.
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 clearly identifies what the tool provides: Amazon's own estimated fees per SKU over the coming weeks, broken out into referral, fulfillment, and storage. It does not use an explicit verb like 'get' or 'list', and it does not distinguish itself from sibling product tools such as product_cogs or pnl_summary.
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?
No guidance is given about when to choose this tool versus alternatives, nor are any exclusions or prerequisites mentioned. The only implicit signal is that the tool is relevant when fee previews are needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.