get_comments

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely non-obvious behavior: an empty list comes with a note when TikTok hides comments from logged-out browsers, and 'top-level' signals replies are excluded. It stops short of mentioning auth or rate-limit 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?

Two short sentences with zero filler. The core capability is front-loaded and the caveat about hidden comments follows in the natural place.

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?

An output schema exists, so return values need not be re-explained, and both parameters are fully documented. The description covers the resource and a meaningful edge case; the only gap is explicit usage/routing guidance.

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% - video_id formats and count bounds are fully documented in the schema - so the baseline of 3 applies. The description adds no syntax, default, or format detail beyond what the schema already states.

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?

States a specific verb and resource ('Get top-level comments on a TikTok video') and names the returned fields (author, text, likes), which sets it apart from every sibling (get_profile, get_videos, search_videos, transcribe_video). The 'top-level' qualifier further scopes the operation precisely.

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?

Usage is implied by the name and resource, but there is no explicit when-to-use or when-not-to-use guidance, nor any routing to alternatives or prerequisites. It is adequate but leaves selection to inference.

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