ytdlp__get_video_comments

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

There are no annotations, so the description carries the transparency burden. It usefully discloses the yt-dlp --write-comments -j command, Python filtering/sorting, maxComments cap, retry cap, and response mode. However, it does not address failure behavior, authentication prerequisites (besides cookies), or potential side effects, leaving gaps.

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 front-loaded with purpose and implementation, followed by a structured @param list. Every line adds useful information, with no filler or unnecessary repetition.

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 7 parameters and no output schema, the description covers all parameters and states the output is structured JSON with at most maxComments entries. It lacks explicit return-field details and caveats about when comments may be unavailable, but overall it provides enough context for correct invocation.

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 0%, but the description provides @param entries for all 7 parameters, including URL format, maxComments range and default, sortOrder enum, cookies, proxy, retry cap, and response mode. This fully compensates for the sparse schema and adds significant meaning beyond the bare property names.

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 'Fetch video comments from a URL using yt-dlp and return structured JSON,' which identifies the specific operation and resource. It does not explicitly differentiate from the sibling tool ytdlp__get_video_comments_summary, so it loses a point for not distinguishing among siblings.

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?

No when-to-use or alternative tool guidance is provided. The description does not mention when to prefer this over ytdlp__get_video_comments_summary or other ytdlp tools, leaving the selection entirely to inference from the tool name.

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