amazon_shop_getGet a creator Amazon Shop storefront by URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public Amazon Shop storefront URL. | |
| cursor | No | Pagination cursor returned by a previous response. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, which cover the operation's safety and dynamic nature. The description adds no further behavioral context (e.g., that it might return a large payload or highlight pagination). With annotations covering the safety profile, a score of 3 is appropriate—the description is consistent but does not enrich beyond the annotations.
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 a single sentence with zero redundancy. It fronts the purpose and method. No wasted words, and it effectively communicates the tool's core function.
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 two-parameter fetch tool with no output schema, the description is sufficiently complete. It states what to provide (URL) and the operation. The cursor parameter is documented in the schema, so its presence is known. The tool seems complete for the intended use; only minor missing context like return format could be added, but it's not critical.
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 100%, so the schema already provides clear definitions for both 'url' and 'cursor'. The description adds no extra meaning about these parameters. Baseline 3 applies because the schema carries the burden, and the description doesn't need to repeat it.
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 states a specific verb ('Get'), a clear resource ('creator Amazon Shop storefront'), and the method ('by URL'). This distinguishes it from the many sibling platform tools, which are all similarly named but target different services. An agent can immediately understand what this tool does and when it applies.
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 clearly implies the tool is used to fetch an Amazon Shop storefront when you have its URL. It does not explicitly mention alternatives or when not to use it, but given the sibling list, there is no direct alternative for Amazon Shop, so ambiguity is minimal. The 'by URL' phrasing sets a clear prerequisite. Cursor for pagination is not mentioned, though it appears in the schema, which slightly reduces guidance.
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 is clearly scoped to a specific platform and action (e.g., facebook_post_get vs instagram_post_get). Descriptions explicitly differentiate similar tools across platforms, and within-a-platform tools like tiktok_search_videos_list vs tiktok_search_hashtag_list have clear disambiguation notes.
All 167 tools follow a strict `platform_resource_action` pattern (e.g., youtube_video_comments_list). No mixing of styles—snake_case throughout, with consistent verb ordering (get, list, search, etc.).
The server has 167 tools, which is far beyond the typical well-scoped range of 3-15. While the broad multi-platform scope justifies many tools, this extreme number makes the tool surface overwhelming and difficult for an agent to navigate efficiently.
The tool set covers a wide range of platforms and operations including profile retrieval, post/video fetching, comments, search, transcripts, and ad library access. Minor gaps exist (e.g., no Facebook events or LinkedIn messaging), but the surface is comprehensive for a read-only data aggregation use case.