Prices for the same ASIN across international Amazon marketplaces. Call when the user asks about cross-market price differences or EU arbitrage opportunities for a product. Costs 1 analyse credit unless the ASIN was analysed in the last 24 hours.
| Name | Required | Description | Default |
|---|---|---|---|
| asin | Yes | ||
| domain | No | GB |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses a cost of 1 analyse credit with a 24-hour cache, which is useful behavioral context. However, with no annotations provided, the description carries the full burden; it omits other behavioral traits like error handling or rate limits for non-cached cases.
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 with no redundancy. First sentence states the purpose succinctly. Second sentence provides usage guidance and cost information. Every word 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?
The description is incomplete for a 2-parameter tool with no output schema. It does not explain the parameters, the return format, or edge cases. While it gives usage context, the missing parameter details and output description leave gaps.
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%, yet the description adds no information about the two parameters ('asin' and 'domain'). It does not explain that 'asin' is required or that 'domain' defaults to 'GB'. The description fails to compensate for the lack of schema descriptions.
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 prices for an ASIN across international Amazon marketplaces. It uses a specific verb ('get') and resource ('prices'), and the context of cross-market price differences distinguishes it from other get_* tools, though sibling differentiation is not explicit.
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?
Explicitly states when to call: 'when the user asks about cross-market price differences or EU arbitrage opportunities'. Does not provide negative usage or alternatives, but the provided context is sufficient for typical AI agent decision-making.
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.
