youtube_transcript

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

With no annotations provided, the description carries the behavioral disclosure burden. It discloses the returned provenance flags (requested_language, actual_language, fallback_used) and makes an explicit behavioral guarantee: 'Never silently swaps languages unless fallback_language is specified.' This meaningfully informs the agent about how language selection behaves.

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 three concise sentences with no filler. The most important information, what the tool extracts and returns, is front-loaded, followed by a useful behavioral guarantee.

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?

The description covers the core behavior, output provenance flags, and language fallback semantics. It is reasonably complete given the detailed input schema and an output schema; it does not cover every edge case like missing captions, but it provides enough for an agent to select and call the 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 baseline is 3. The description adds some value by explaining the fallback language behavior and provenance flags, but it does not substantially elaborate on translate_to or include_timestamps beyond what the schema already states.

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 opens with a specific verb and resource: 'Extract the spoken transcript of a YouTube video.' It also clarifies the output includes timestamped segments and language provenance, which immediately distinguishes this from sibling tools like youtube_search or youtube_video.

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 purpose implies this tool is for retrieving a video's transcript, and the wording 'Extract the spoken transcript' gives reasonable context. However, it does not explicitly state when to prefer this over alternatives such as youtube_find_in_video, nor does it mention exclusions or conditions for selection.

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