rumble_video_comments_listList top-level comments on a Rumble video. Accepts a video URL. Returns a list (use cursor when paginated).
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Link to the Rumble video. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and openWorldHint=true, so the description's additional mention of returning a list and using a cursor for pagination adds useful behavioral context. However, it does not disclose error conditions, rate limits, or how the cursor parameter is supplied (it is not in the schema). A score of 3 reflects partial added value beyond 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 succinct with three short, information-dense sentences. Purpose is front-loaded, and no redundant information is present. It earns full marks for efficiency.
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 list tool with one parameter, no output schema, and read-only annotations, the description covers the core behavior: lists top-level comments, accepts a video URL, returns a list, and suggests cursor pagination. It does not describe the structure of each comment (e.g., fields like text, author, timestamp), which could be inferred from context but is a minor gap.
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 parameter is fully described in the schema ('Link to the Rumble video.'), and the tool description repeats this ('Accepts a video URL.'). No additional format, validation, or examples are provided. With 100% schema coverage, the description adds minimal semantic value beyond the schema.
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 action (list top-level comments) on a specific resource (Rumble video), clearly distinguishing it from sibling tools like rumble_video_get (fetch video details) and rumble_channel_videos_list (list videos in a channel). The qualifier 'top-level' clarifies the scope.
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 implies that a video URL is required and that it lists comments, but does not mention when not to use it (e.g., for replies) or any prerequisites. Sibling comment tools on other platforms exist, but no cross-referencing is done.
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.