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BACH-AI-Tools

BACH YouTube API MCP Server

comments

Retrieve comments and discussion threads from YouTube videos or shorts, supporting pagination, sorting, and regional localization.

Instructions

Get video's or shorts' comments/thread. Quota cost is 1 unit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesVideo Id or Shorts Video Id
tokenNoPagination token Alternatively, use X-TOKEN in header
sort_byNoAvailable options: newest top [default]
geoNoISO 3166-2 country code of the region. Like US (default), GB, CA, IN, etc.
langNoLocale/language for request. Like en, gb, hi, etc
X-CACHEBYPASSNoCache bypass, the value must be 1 Quota Cost +1
X-TOKENNoAlternative way to pass Pagination token via headers. This will solve 414, URI too long issue.
Behavior3/5

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 quota cost (1 unit) and hints at pagination via 'token', which adds some behavioral context. However, it lacks details on rate limits, authentication needs, error handling, or what the return format looks like (e.g., comment structure, pagination behavior). The description doesn't contradict annotations (none provided).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief and front-loaded with the core purpose in the first sentence, followed by quota information. It wastes no words, but could be slightly more structured (e.g., separating purpose from behavioral notes). Overall, it's efficient but not perfectly optimized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (7 parameters, no annotations, no output schema), the description is minimally adequate. It covers the basic purpose and quota cost but lacks details on output format, error cases, or integration with sibling tools. Without annotations or output schema, more context on behavior and results would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema (e.g., it doesn't explain 'id' further or provide examples for 'sort_by'). Baseline is 3 since the schema does the heavy lifting, but the description doesn't compensate with extra insights.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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 video's or shorts' comments/thread.' It specifies the verb ('Get') and resource ('comments/thread'), and distinguishes the target (videos/shorts) from other content types. However, it doesn't explicitly differentiate from sibling tools like 'post_comments' or 'channel_community_posts', which might handle comments for different content types.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 mentions quota cost but doesn't specify scenarios where this tool is preferred over similar tools like 'post_comments' or in what context it should be invoked. No exclusions or prerequisites are mentioned.

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

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