google_youtube_list_commentsRetrieve comment threads for a YouTube video, ordered newest first. Use it to read viewer feedback and discussions through an AI agent.
List comment threads for a video, most recent first.
| Name | Required | Description | Default |
|---|---|---|---|
| account | No | Account nickname to use. | |
| videoId | Yes | YouTube video ID. | |
| maxResults | No | Max results (default 20). |
Changes observed during successful MCP inspections.
v0.1.60Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It adds only ordering ('most recent first'); it says nothing about pagination, result caps, authentication/account requirements, or whether replies are included in threads. For a list tool with zero annotation coverage, that is a meaningful gap.
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?
A single front-loaded sentence with the ordering constraint appended; no filler or redundancy. Every clause earns its 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?
For a simple read-only list tool with a fully-described schema and no output schema, the definition is minimally sufficient, but with no annotations and no output schema it should mention pagination behavior and the default/max results to be fully callable without guesswork.
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%, so the parameters (videoId, account, maxResults) are already documented in the schema. The description's 'for a video' only loosely reinforces the required videoId and adds no format or range detail beyond the schema. Baseline 3 is correct.
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 (list) and resource (comment threads for a video), which is clear and distinguishable from write-side siblings like google_youtube_insert_comment or google_youtube_mark_comment_spam. It falls short of a 5 because it doesn't explicitly name what it is not (e.g., it doesn't clarify thread vs. reply structure) beyond the verb.
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 purpose implies the reading context (fetch comments for a given video), so usage is inferable, but there is no explicit when-to-use, no exclusions, and no pointers to siblings such as insert_comment for posting. Adequate but leaves routing to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.