Search Amazon by product title via Keepa and return the top matching ASINs with thumbnails. Call when the user names a product without an ASIN or barcode; present the candidates and let them pick before analysing. limit is 1-10.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| title | Yes | ||
| domain | No | GB |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full responsibility. It discloses the tool uses Keepa, returns top matches with thumbnails, and limits results to 1-10. It does not cover rate limits, error handling, or data freshness, but adequately describes the core behavior for a search tool.
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 well-structured sentences. The first states the core function, the second gives usage guidance, and the third adds parameter detail. Every sentence is valuable and front-loaded.
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's simplicity (3 parameters, no output schema), the description covers the usage scenario, parameter constraints, and result format (ASINs with thumbnails). It is complete enough for an agent to use correctly, though it lacks explicit mention of domain valid values or error cases.
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 coverage is 0%, so the description must compensate. It adds meaning by stating 'limit is 1-10' which clarifies the range for the limit parameter. However, it does not explain the domain parameter (likely Amazon marketplace country code) or add detail about the title parameter beyond the obvious. This provides partial but incomplete parameter context.
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 the tool searches Amazon by product title via Keepa and returns top matching ASINs with thumbnails. This distinguishes it from siblings like lookup_by_ean which searches by barcode, and analyse_product which analyzes existing ASINs.
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 guidance: 'Call when the user names a product without an ASIN or barcode; present the candidates and let them pick before analysing.' This tells the agent when to use the tool and outlines the workflow, implying alternatives exist when ASIN or barcode is known.
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.
