Repricer dashboard summary: total/active SKU counts, per-status breakdown, Buy Box wins and win %, items matching the Buy Box exactly, units actively repricing and the last update time. Call first for broad questions like 'how's the repricer doing?'.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description carries the full burden of behavioral disclosure. It thoroughly specifies the data returned (SKU counts, per-status breakdown, Buy Box stats, last update time), making the tool's behavior transparent. It does not explicitly state it is read-only, but that is strongly implied by the summary nature, and no side effects are suggested.
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 compact: one sentence enumerating the summary components and one sentence giving usage direction. It is front-loaded with 'Repricer dashboard summary' and contains no filler or redundant rephrasing of the tool name.
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 zero-parameter tool with no output schema, the description is remarkably complete. It lists all the key metrics that will be returned, making it easy for an agent to know exactly what to expect without needing additional documentation.
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 tool has zero parameters, so per the rubric the baseline is 4. There is nothing to explain beyond the schema, and the description already clarifies what the returned statistics represent.
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 identifies this as a repricer dashboard summary with a specific verb ('Call first') and enumerates exactly what metrics are included (total/active SKU counts, per-status breakdown, Buy Box wins/win %, etc.). It distinguishes itself from sibling repricer tools like get_repricer_items and get_repricer_log by focusing on a high-level overview.
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 provides explicit guidance: 'Call first for broad questions like "how's the repricer doing?"' This establishes a clear use case. However, it does not explicitly name alternative tools for detailed queries, so it stops short of a full when-not-to-use explanation.
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.
