get_comments_by_id_likes

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

Annotations already cover read-only, idempotent, and non-destructive behavior, so the description doesn't repeat those. It adds useful behavioral details about pagination: default limits, maximum caps, and clamping behavior. This goes beyond the annotations and helps the agent anticipate response size and pagination handling.

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: a one-line purpose, the endpoint, and an Args list with clear parameter explanations. No redundant fluff, but the pagination details could be slightly more compact. Still, it is efficient and front-loaded with the core purpose.

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 GET endpoint with an output schema present, the description covers the essential information: purpose, parameters, and pagination behavior. It doesn't mention any special cases like authentication or rate limits, but those are not required given the annotations and simplicity. It is sufficiently complete for an agent to call it correctly.

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 schema provides only titles ('Id', 'Page', 'Limit') with no descriptions, so schema coverage is 0%. The description compensates fully by explaining each parameter: id is the resource id/slug, page is the page number, and limit includes details on defaults, maximums, and clamping. This gives the agent complete understanding of the parameters.

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 all users who liked a comment.' It specifies the resource (comment by id) and the action (retrieving likers), and the endpoint URL reinforces the scope. It is easily distinguishable from sibling tools like get_comments_by_id_replies or get_comments_by_id_reactions.

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 no guidance on when to use this tool versus alternatives. It doesn't mention any conditions, exclusions, or specific scenarios. The agent is left to infer usage from the name and endpoint alone, without contextual differentiation from similar comment-related endpoints.

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