get_video_comments

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the sorting method ('by relevance') and included fields (author, comment text, like count, publish date), which adds some context. However, it fails to disclose critical behavioral traits such as whether this is a read-only operation, potential rate limits, authentication requirements, or error handling, which are essential for a tool interacting with an external API like YouTube.

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 concise and well-structured, consisting of two sentences that efficiently convey the core functionality and use case. The first sentence covers the main purpose and key features, while the second provides application context. There's no redundant or wasted language, making it easy 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?

Given the complexity of a video comments tool with no annotations and no output schema, the description is moderately complete. It covers the basic purpose, sorting, and included fields, but lacks details on output format, pagination, error cases, or API-specific behaviors. For a tool that likely interacts with an external service like YouTube, more contextual information would be beneficial to ensure reliable usage.

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 input schema has 100% description coverage, with clear documentation for both parameters (video_id and limit). The description doesn't add any parameter-specific details beyond what the schema provides, such as explaining the relevance sorting algorithm or comment filtering logic. Given the high schema coverage, a baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 the tool's purpose: 'Returns top-level comments for a video, sorted by relevance.' It specifies the verb ('returns'), resource ('top-level comments for a video'), and key attributes like sorting and included fields. However, it doesn't explicitly differentiate from sibling tools like 'get_comment_keywords' or 'get_video_details', which prevents a perfect score.

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 provides implied usage context by stating it's 'Useful for audience sentiment and feedback analysis,' which suggests when to use this tool. However, it lacks explicit guidance on when to choose this over alternatives like 'get_comment_keywords' or 'get_video_details', and doesn't mention prerequisites or exclusions, leaving room for ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.