appleMusic_artist_getGet an Apple Music artist by id or artist URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | No | Optional Apple Music artist URL for the request. | |
| artistId | No | Optional Apple Music artist id for the request. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the description only needs to add context beyond those. It confirms it's a read operation but adds no details about rate limits, pagination, or what happens with invalid inputs. This is adequate given the simple read-only nature and annotation coverage.
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, clear sentence with no unnecessary words. The essential information (action, resource, and how to specify it) is front-loaded and immediately understandable.
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 and lack of an output schema, the description is minimally complete. It doesn't specify what the response contains (e.g., artist details like name, genres), but for a straightforward get operation this might be sufficient. A bit more detail about the return value would improve completeness.
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 100%, so both parameters (url and artistId) already have descriptions. The tool description adds little beyond repeating that either an id or URL can be used; it doesn't clarify that at least one is required or what happens if both are provided. This meets the baseline but adds minimal value.
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 action (Get), the resource (Apple Music artist), and the two ways to specify it (by id or URL). It distinguishes the tool from siblings like appleMusic_album_get and appleMusic_track_get by naming the specific resource type.
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?
No explicit guidance on when to use this tool versus alternatives. It doesn't mention that search (appleMusic_search_list) should be used when an id or URL is unknown, nor does it state any prerequisites or exclusions. The usage is only implied by the description.
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.