tiktok_music_videos_listList TikTok videos that use a specific music clip. Accepts a clip id. Returns a list (use cursor when paginated).
| Name | Required | Description | Default |
|---|---|---|---|
| clipId | Yes | TikTok music clip id whose videos should be listed. | |
| cursor | No | Pagination cursor returned by a previous response. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and openWorldHint, so the description adds value by disclosing that it returns a list and that pagination is handled via a cursor. It doesn't contradict annotations. The pagination note is a useful behavioral detail beyond the schema.
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?
Two concise sentences with the core purpose stated first. No filler or redundant phrasing. The pagination note is placed appropriately at the end, keeping the most important information front-loaded.
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 list tool with no output schema, it covers the input requirements, return type (list), and pagination behavior. It lacks details like ordering or result limits, but these are not critical for an initial call. The openWorldHint is not explicitly addressed, but the list scope is clear.
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% (both parameters have descriptions). The description reiterates that it accepts a clip id and mentions cursor for pagination, which the schema already documents. It adds minimal new meaning, so the baseline of 3 is appropriate.
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 ('List') and resource ('TikTok videos that use a specific music clip'), which clearly distinguishes it from other tiktok_*_list tools that list videos by profile, search, or trend. The title and name reinforce the purpose, making it unambiguous.
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 implies when to use it (when you have a music clip id) but does not explicitly mention alternatives or exclusions. For example, it doesn't say 'use this instead of tiktok_profile_videos_list for music-specific filtering.' The guidance is adequate but not explicit.
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.