get_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 adds valuable context beyond the input schema: it specifies the return data (comment author, text, like count, reply count), mentions an environment variable requirement (YOUTUBE_API_KEY), and hints at the tool's utility. However, it lacks details on error handling, rate limits, or pagination behavior.

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 appropriately sized and front-loaded: it starts with the core purpose, then lists return values, prerequisites, and utility in three concise sentences. Every sentence adds value without redundancy, making it efficient and well-structured.

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 tool's moderate complexity (3 parameters, no output schema, no annotations), the description is fairly complete. It covers purpose, return data, prerequisites, and utility, but lacks output format details (e.g., structure of returned comments) and error scenarios. Since there is no output schema, some gaps remain in fully describing the tool's behavior.

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, providing clear details for all parameters (url, maxResults, order). The description does not add any parameter-specific semantics beyond what the schema already explains, such as format examples or usage tips. According to the rules, with high schema coverage (>80%), the baseline is 3 even without param info in the description.

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: 'Get top comments from a YouTube video.' It specifies the resource (YouTube video comments) and the verb (get), but does not explicitly differentiate from sibling tools like get_video or get_audio, which target different resources. This makes it clear but not fully sibling-distinctive.

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: 'Useful for understanding audience reactions and discussion topics.' This suggests when to use it (for analyzing video engagement), but does not explicitly state when not to use it or name alternatives among sibling tools. No explicit exclusions or comparisons are given.

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