youtube_video_getGet a single YouTube video by URL. Channel lives under channel (not author); publish time is publishedAt.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Link to the YouTube video. Shorts URLs are also supported. | |
| language | No | Optional preferred language for returned text when the source supports localization. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and the description does not contradict this. It adds valuable context about the response structure—clarifying that the channel field is named 'channel' (not 'author') and the publish time is 'publishedAt'—which helps agents interpret results correctly. This goes beyond annotations without conflicting with them.
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 composed of two efficient sentences. The first sentence delivers the primary purpose, and the second adds two useful field clarifications without fluff. It is front-loaded and every word contributes value, though it slightly exceeds the minimal needed length.
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 get tool with only two parameters and no nested objects, the description is largely complete. It conveys the core operation and clarifies response field naming. It does not describe return format in detail, but given the tool's simplicity and the presence of annotations, what is missing is minor.
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% for both parameters (url and language), each with detailed descriptions. The tool description adds no extra semantic detail beyond what the schema already provides—it merely restates 'by URL' and offers field clarifications unrelated to parameters. Thus, 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 clearly states a specific verb ('Get') and resource ('a single YouTube video by URL'), immediately distinguishing it from sibling tools like youtube_channel_get or youtube_playlist_get. It also narrows scope with 'single' and provides a pointer to the URL parameter, leaving no ambiguity about what this tool retrieves.
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 usage through its clear purpose, but it does not explicitly mention when to use this tool versus alternatives (e.g., youtube_video_comments_list for comments, youtube_video_transcript_get for transcripts). No exclusions or when-not guidance is given. The field clarifications (channel, publishedAt) hint at output expectations but not at selection criteria.
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.