Best time to publish

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

Annotations already declare this a read-only, idempotent, open-world operation, so the safety bar is low; the description goes further by disclosing the derivation method (relative performance against neighbouring uploads) and that the output carries confidence and sample-size caveats. It stops short of stating rate limits or what happens with sparse history, but the methodological disclosure is genuine added context.

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 compact sentences with the core capability front-loaded and the caveat trailing. The closing clause about confidence and sample sizes leans on output content that an output schema already exposes, so it earns its place only partially.

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?

With an output schema present, the description needn't enumerate return fields, and it correctly focuses on methodology and trustworthiness signals. What remains thin is the operational prerequisite — how much upload history is needed before a recommendation is meaningful — which an agent would want before calling.

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% and each parameter (format, channel_id, timezone_name) is documented with defaults and examples, so the baseline applies. The description adds nothing parameter-specific — notably it does not reinforce the schema's hint that analyzing Shorts and long-form separately gives better results.

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 — 'recommend the best weekday and time block to publish' — plus the inference basis ('how your past uploads performed relative to neighbouring uploads'). This is clearly distinct from the sibling analytics tools (youtube_get_channel_analytics, youtube_get_video_analytics), which report metrics rather than prescribe a scheduling slot.

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 description implies the use case (planning when to publish) and mentions validation, but never explicitly says when to call this versus the analytics siblings, nor what prerequisites apply (e.g. minimum upload history). Usage is inferable from the name and purpose statement rather than stated.

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