Per-SKU profitability over the last N days: units, revenue, profit, ROI, return rate, current price vs break-even and a selling-at-a-loss flag. Call for 'which products make or lose me money?' or 'what's selling below break-even?'. days 7-365. Requires a connected Amazon account.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It implies a read-only operation (getting performance data) and states a required connection, but does not explicitly confirm read-only status, rate limits, or other behaviors.
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?
Two sentences, no fluff. The first sentence lists what the tool returns, the second provides usage rationale and constraints. Every sentence adds value.
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 a simple tool with one parameter and no output schema, the description covers the purpose, parameter range, and the metrics returned. It could mention pagination or ordering, but the information provided is sufficient for an agent to understand the tool's output.
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?
The single parameter 'days' has a default of 30 in the schema, but the description adds the valid range (7-365) and explains it as the time period for the data. This adds significant meaning beyond the schema, which has 0% coverage.
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 provides per-SKU profitability metrics over a time period, listing specific fields (units, revenue, profit, ROI, return rate, price vs break-even, selling-at-a-loss flag). This distinguishes it from siblings like calculate_profit or get_best_sellers.
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?
The description explicitly tells when to use the tool ('which products make or lose me money?' or 'what's selling below break-even?') and notes the prerequisite of a connected Amazon account. It does not provide explicit when-not guidance, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.
