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

No annotations are provided, so the description carries the full burden. It discloses pagination, ordering, and the fact that it returns top-level comments. However, it does not mention authentication requirements, rate limits, or the possibility of empty results.

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: two sentences that cover purpose, output, usage context, and pagination. Every sentence adds value without redundancy.

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 low complexity, lack of output schema, and no annotations, the description provides adequate information: what it returns (comments with likes and authors), how to paginate (cursor), and a use case. Missing details about error states or limits, but acceptable.

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?

All four parameters are well-described in the schema (100% coverage). The description adds minimal extra context (e.g., relevance ordering, pagination behavior) but does not significantly enhance understanding beyond the schema.

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 action (list), resource (top-level comments), ordering (most-relevant first), and included data (like counts and authors). It effectively distinguishes from the sibling tool tiktok_comment_replies, which handles nested replies.

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 explicit use cases (sentiment sampling, audience-response analysis) and mentions pagination via cursor. It does not explicitly state when not to use, but the purpose is clear enough to avoid confusion with siblings.

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