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

With no annotations, the description carries the full burden of behavioral disclosure. It clearly indicates a read-only fetch and provides rich output semantics: raw + normalized views/likes, safety/unlisted flags, captions with kind:asr, Content-ID music matches, social links, and related rails. It omits error handling, auth, and rate limits, but for a GET-style data tool the described behavior is substantially transparent.

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?

The description is long but information-dense: it front-loads the core purpose, then systematically lists return fields and use cases without filler. It could be structured into shorter sentences, but every clause adds relevant information for a tool with a rich payload.

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?

Given no output schema and no annotations, the description compensates well by enumerating the full return surface and tying usage to the transcript sibling. Minor gaps remain around error cases and access requirements, but an agent has enough to invoke the tool correctly for typical metadata enrichment tasks.

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 all four parameters (v, gl, hl, deviceType) are already documented with types, examples, and allowed values. The description only repeats the videoId concept and does not add meaning beyond the schema, so baseline 3 is appropriate.

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 states a specific verb ('Fetches') and resource ('a single YouTube video by its 11-character videoId') and enumerates the returned fields in detail. It is clearly distinct from the sibling channel/search/transcript tools because it is scoped to video metadata.

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 lists concrete use cases: enriching video URLs, monitoring view/like growth, extracting music or affiliate links, building recommender/RAG features, and detecting caption tracks before calling the YouTube Transcript endpoint. It does not explicitly state when not to use the tool, but the context is clear enough for an agent to select it.

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