The user's price-alert notifications from their A2A monitor tasks, grouped by task. Call when the user asks what alerts or notifications they have. show_checked: 'unchecked' (default), 'checked' or 'all'.
| Name | Required | Description | Default |
|---|---|---|---|
| show_checked | No | unchecked |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It implies read-only retrieval but does not explicitly state no side effects, required permissions, rate limits, or behavior when no notifications exist. The description is insufficient to fully understand tool behavior.
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 two concise sentences with the purpose front-loaded. The second sentence could be more structured but is efficient and contains no fluff.
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 query tool with one non-required parameter and no output schema, the description explains what is returned (notifications grouped by task) and the filter option. However, it lacks details on response format or limits, leaving minor 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?
The single parameter show_checked is fully explained in the description with its allowed values and default, adding meaning beyond the schema's title and default value. Despite 0% schema coverage, the description compensates well.
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 retrieves price-alert notifications from A2A monitor tasks, grouped by task. This specific verb+resource combination distinguishes it from sibling tools like get_price_monitors and mark_notification.
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 says 'Call when the user asks what alerts or notifications they have,' providing clear usage context. However, it does not mention when not to use it or compare to alternative notification-related tools among siblings.
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.
