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

Annotations already mark this as readOnly and non-destructive, so the description's main value is beyond that. It discloses that the request is metered and may take longer when captions need resolving, which is additional operational context not present in annotations. It does not contradict annotations.

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 brief and well-structured. The first sentence states the core purpose, and the second adds important context about metering and latency. It avoids unnecessary verbosity, though it could be slightly more explicit about usage guidelines. The information is front-loaded and scannable.

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 the tool has an output schema (mentioned in context), the description doesn't need to detail return values. It covers the key aspects: normalization, timestamped segments, caption languages, and metering. However, it could benefit from specifying the default language behavior (e.g., 'auto' meaning auto-detect) and any limitations (e.g., videos without captions). The description is adequate but leaves some gaps.

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 0%, so the description must compensate. It explains that the tool returns timestamped segments and available caption languages, providing meaning for the 'language' parameter (caption language) and the output. However, it doesn't explicitly state the format of the video_id, but the schema already provides a regex pattern. This is a strong compensation for the lack of schema descriptions.

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 clearly states the function: fetches a normalized transcript for a YouTube video ID. It specifies the resource (YouTube video transcript) and the verb (fetch). While it does not explicitly distinguish from siblings like get_youtube_channel_transcripts, the focus on a single video vs. channel transcripts is apparent from the name and description.

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 provides useful context: it mentions the request is metered and may take longer when captions must be resolved, which implies use cases where the user accepts potential latency. However, it does not explicitly state when to use this tool versus alternatives like get_youtube_channel_transcripts, nor does it provide exclusions or specific scenarios.

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