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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint=false and destructiveHint=false, so the safety profile is covered. The description adds that results are AI-scored and what scoring dimensions exist, but omits any mention that the call is paid (x_payment is required) and that sampling is capped at 12 videos — meaningful behavioral context for invocation.

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 short, front-loaded sentences with no filler; the core action leads and the scoring dimensions follow. The second line is a fragment but reads cleanly and earns its place by naming the outputs.

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?

An output schema exists, so return values need no explanation, and annotations cover the safety profile. The definition is nearly complete for a read-only research tool; the only real omission is failing to surface the paid-transaction prerequisite outside the schema.

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 keyword, x_payment, and num_videos are all documented in the schema itself. The description adds no syntax, format, or constraint details beyond that (e.g., it does not restate the max-12 cap or the payment payload format), so baseline 3 applies.

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 concrete verb+resource ('scrape top YouTube videos by views for any keyword') and enumerates the AI scoring dimensions, so the agent knows exactly what the tool produces. It does not, however, distinguish itself from close siblings like search_and_rank_videos or analyze_youtube_topic, which occupy similar territory.

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 keyword-research framing and the opportunity/saturation output imply when this tool is useful (picking a niche), but there is no explicit when-to-use, when-not-to-use, or named alternative. Usage must be inferred from the output list rather than stated.

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