Get Twitch clip
twitch_clip_getGet metadata and playback URLs for a Twitch clip by URL.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Link to the Twitch clip. |
twitch_clip_getGet metadata and playback URLs for a Twitch clip by URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Link to the Twitch clip. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds that it returns metadata and playback URLs, which is more specific than the tool name, but does not disclose behavioral caveats like rate limits, auth needs, or error handling. Given the annotations cover read-only safety, the additional context is minimal, so a 3 is appropriate.
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?
One efficient sentence front-loads the action and resource. It includes the key output info and wastes no words. Perfectly concise for a single-purpose read tool.
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, single-parameter, read-only tool with annotations covering safety and no output schema, the description is complete: it states what it returns and how to invoke it (by URL). An agent has everything needed to call it correctly without further elaboration.
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% – the single 'url' parameter is described as 'Link to the Twitch clip.' The description's phrase 'by URL' simply echoes the schema. No extra semantic detail is added, so baseline 3 for high coverage applies.
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 specific resource (Twitch clip), and the concrete outputs (metadata and playback URLs). It clearly distinguishes this from sibling Twitch tools like twitch_profile_get or twitch_profile_videos_list, which target different resource types (profiles, videos). No ambiguity.
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 the use case: when you have a Twitch clip URL and want its metadata/playback URLs. It does not explicitly name alternatives or conditions (e.g., 'use this for clips, not for profile or videos'), but the context is clear enough for an agent to select it appropriately among many platform-specific get tools. Lacks explicit exclusions, so not a 5.
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.