Video Sponsors

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

Adds substantial context beyond the annotations: it is experimental, consumes paid API credits, requires confirm=true, and explicitly clarifies the 'read-like POST does not publish to social platforms' point that reconciles with readOnlyHint=false. It also discloses that results are inferred, not an official field. Only the absence of detail on latency/pagination keeps it from a 5.

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?

Front-loaded with 'Experimental endpoint' and the core purpose, then layering caveats in a sensible order. Slightly long, and the feedback email sentence is filler, but nearly every sentence carries useful information.

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 no output schema, the description steps in by describing the return (suspected sponsors with confidence and evidence) and the inference caveat. Combined with annotations covering the safety profile and a fully documented schema, an agent has enough to call this tool correctly.

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 schema already documents url, account, confirm, and language. The description only reiterates the confirm=true requirement (adding the cost linkage), leaving account and language unexplained. Baseline 3 is appropriate when the schema does the heavy lifting.

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 (checks a YouTube video for paid-promotion disclosure, infers likely sponsors) and explains the inference mechanism (description, links, promo-code text, transcript). It distinguishes itself from siblings like youtube_transcript and youtube_video_short_details by naming the exact artifact it returns (suspected sponsors with confidence and evidence).

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?

Marks the tool as experimental and states the operating constraint (requires confirm=true, consumes paid credits), which frames when it is worth invoking. However, it never names an alternative tool or an explicit when-not condition, so routing vs youtube_transcript or youtube_video_short_details is left to inference.

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