The user's Amazon orders with fees and COGS-based profit. Call for questions like 'how are sales today?' or 'show orders for this SKU'. timeframe: today, yesterday, week, month; or use date_from/date_to (YYYY-MM-DD). Requires a connected Amazon account (closed beta).
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No | ||
| search | No | ||
| status | No | ||
| date_to | No | ||
| date_from | No | ||
| timeframe | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It discloses the output includes fees and profit, and that a connected account is required. However, it does not mention pagination behavior, rate limits, or what happens if no results. It also fails to describe how the 'search' parameter works beyond implying SKU filtering.
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 three sentences with no wasted words. It front-loads the purpose, then provides example queries, then details parameters and requirements. Each sentence earns its place.
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?
Given the tool has 7 parameters, no output schema, and many siblings, the description is incomplete. It fails to describe pagination, status filtering, and return structure. It provides enough context for basic use but leaves agents guessing on important details.
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 0%, so description must compensate. It adds meaning for timeframe and date_from/date_to (format YYYY-MM-DD) and suggests 'search' is for SKU. But it does not explain 'page', 'limit', or 'status' parameters, leaving significant gaps.
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 states it retrieves the user's Amazon orders with fees and COGS-based profit. It provides example use cases like 'how are sales today?' and 'show orders for this SKU', clearly differentiating it from siblings like dashboard summary or inventory.
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?
It specifies when to call the tool (questions about sales, orders for a SKU) and gives context about timeframes (today, yesterday, week, month) or date range. It also mentions a prerequisite (connected Amazon account). However, it does not explicitly state when not to use it or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct data type or action (e.g., product analysis, deal types, FBA operations). Even similar-sounding tools like get_deal_results and get_oa_deals are clearly separated by domain (A2A vs OA) in descriptions. No significant overlap.
All tools follow a clear verb_noun pattern with underscores (e.g., analyse_product, create_deal_task, get_credits). The consistent 'get_' prefix for retrieval tools and varied but predictable action verbs make the set easy to navigate.
At 37 tools, the set is large but covers a broad Amazon seller ecosystem (research, sourcing, FBA, deals, monitoring). Each tool serves a distinct purpose, and the count reflects the domain's complexity without being bloated.
The tool surface covers all major seller workflows: product analysis, profit calculation, sourcing, deal discovery, storefront monitoring, FBA operations, purchase tracking, price alerts, and reconciliation. No obvious gaps for core tasks.
