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

Annotations already establish a safe read operation (readOnlyHint=true, destructiveHint=false, openWorld=true), and the description adds real behavioral context: the inference sources (description, description links, promo-code text, transcript), confidence/evidence in the response, and that repeated requests may re-purchase data. The cost statement is self-contradictory, saying 'at least 10 Nexscope credits' and then '1 credit per request,' which reduces trust in that disclosure.

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 sentences give zero waste: the scoping constraint is front-loaded ahead of the alternative.

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?

Complete for a filtered-list tool whose annotations already carry the safety profile; nothing an agent needs in order to call it correctly is missing.

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 url and language parameters are already documented in the schema. The description implies transcript lookup drives the language parameter but adds no format or default guidance beyond the schema, so the baseline of 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?

The description uses a specific verb and resource: it checks a YouTube video for paid-promotion disclosure and infers likely sponsors. It also explicitly contrasts itself with the official YouTube sponsor field and with the video metadata itself, making the purpose distinct from sibling lookups such as social_youtube_video_detail or social_youtube_transcript.

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?

It states this is an experimental, inferred endpoint and that results are suspected, not official, so the agent knows it is a best-effort enrichment call. However, it never says when to prefer this over social_youtube_video_detail or social_youtube_transcript, nor does it set preconditions (for example, that disclosure may be absent).

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