Get Twitch profile
twitch_profile_getGet a Twitch profile for a channel by handle.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| handle | Yes | Twitch handle to look up, with or without a leading @. |
twitch_profile_getGet a Twitch profile for a channel by handle.
| Name | Required | Description | Default |
|---|---|---|---|
| handle | Yes | Twitch handle to look up, with or without a leading @. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, covering the safety profile. The description adds no behavioral context beyond what annotations provide—no mention of return format, pagination, or edge cases. Given the annotations carry the safety burden, the description is adequate but contributes minimal extra behavioral disclosure.
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, front-loaded sentence with no filler. It states the action, resource, and key input in six words, making it maximally concise and well-structured for an agent to parse quickly.
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 read-only tool with one parameter and no output schema, the description is minimally sufficient. However, it does not indicate what kind of data the profile contains (e.g., followers, bio, channel stats) or clarify that it excludes schedule/videos (which have separate tools). Slightly more context would help an agent decide if this is the right tool for a specific piece of profile data.
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% and already explains the handle parameter (including optional '@'). The description's 'by handle' merely reiterates the parameter, adding no new meaning. With full schema coverage, the baseline of 3 applies; the description does not compensate with extra detail.
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 clear verb ('Get') and a specific resource ('Twitch profile') and identifies the lookup method ('by handle'). It is distinguishable from sibling tools like twitch_profile_schedule_get and twitch_profile_videos_list primarily through the tool name, since the description does not explicitly contrast them, but the purpose is 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 usage context is implied: use this when you need a channel's profile information. However, it does not mention when not to use it or point to alternatives among the sibling Twitch tools (e.g., schedule, videos). There is no explicit when/when-not guidance, only the basic purpose.
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.