Recent repricer price changes, newest first: SKU, old → new price, the reason, the reference price it repriced against (Buy Box / lowest FBA) and whether the floor or ceiling capped the move. Call when the user asks what the repricer changed recently or why a price moved. limit max 500.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | ||
| limit | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the output fields, ordering (newest first), and a limit cap (max 500). However, it does not explicitly state that this is a read-only operation, define 'recent,' or explain pagination behavior with the page parameter, leaving some ambiguity.
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 concise (~60 words) and well-structured, front-loading the output content, then the usage trigger, then the limit constraint. Every sentence adds value with no redundancy.
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 tool lacks an output schema and annotations, so the description must compensate. It covers the main output fields and the limit cap, but misses pagination behavior, the meaning of 'recent,' and the overall response structure. Given these gaps, the description is minimally sufficient but not complete.
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 parameter descriptions are absent (0% coverage), so the description must compensate. It only mentions 'limit max 500,' which conveys a constraint on the limit parameter, but completely omits the page parameter and fails to explain how limit and page control the result set. This is insufficient for an agent to understand the parameters.
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 returns recent repricer price changes, with specific fields listed (SKU, old→new price, reason, reference price, floor/ceiling cap). This distinguishes it from sibling tools like get_repricer_items or get_repricer_stats, which focus on current items or statistics.
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 explicitly says 'Call when the user asks what the repricer changed recently or why a price moved,' giving a clear trigger context. However, it does not mention when not to use this tool or point to alternatives like get_repricer_stats for summary data, so it falls short of a perfect 5.
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.
