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yt_reply_comment

Publish a public reply to a top-level YouTube comment under the authenticated channel identity. Provide the top-level comment ID and reply text to respond directly in the comments thread.

Instructions

Publish a public reply to a top-level comment (comments.insert, ~50 quota units) under the authenticated channel identity. parent_id must be a top-level commentId from yt_list_comments. Non-idempotent. Built-in limits (not adjustable): at most 20 comments+replies per rolling hour and 100 per rolling 24 hours, and the same text at most 2 times per 24 hours.

Input Schema

NameRequiredDescriptionDefault
textYesPlain-text reply body.
parent_idYescommentId of the top-level comment to reply to.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.7.0

TDQS

A4.6/5.0
Behavior5/5

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

Beyond annotations it discloses quota cost (~50 units), the acting identity (authenticated channel), that the reply is public, and concrete non-adjustable rate limits (20/hour, 100/24h, same text max 2x/24h) — exactly the information needed to avoid retry storms against a write endpoint. The only redundancy is "Non-idempotent," which merely restates idempotentHint=false.

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

Conciseness5/5

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

Four short sentences, front-loaded with the action and API call, then prerequisite, then idempotency, then limits. No filler and no repetition of schema constraints such as maxLength.

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

Completeness4/5

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

For a two-parameter write tool with annotations covering safety and openness, the description supplies quota, rate limits, and identity, which is most of what an agent needs. Minor gaps remain: it does not say what is returned (no output schema exists) or what happens when a limit is exceeded, so the agent cannot tell success signals from throttling failures.

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

Parameters4/5

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

Schema coverage is 100%, so the schema already carries the baseline meaning of both parameters. The description adds real value by pinning down the provenance and constraint of parent_id (a top-level commentId sourced from yt_list_comments) rather than any comment id, which prevents a common misuse; it says nothing extra about text beyond the schema's length bounds.

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

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Publish a public reply to a top-level comment") plus the underlying API call (comments.insert). The phrase "top-level comment" and the pointer to yt_list_comments lets an agent separate this from yt_post_comment and the other post/upload siblings without opening a schema.

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

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a clear when-to-use condition (replying beneath an existing top-level comment) and a hard prerequisite: parent_id must be a top-level commentId obtained from yt_list_comments, which implicitly excludes replying to a reply. It stops short of naming yt_post_comment as the alternative for creating top-level comments, so routing is inferred rather than spelled out.

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