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

Goes well beyond the readOnly/openWorld/idempotent annotations: manual captions preferred with auto-generated fallback, optional translation, no charge for videos lacking captions or on errors, and the x402 USDC payment model at $0.002 per successful call including the 'call without payment to receive the PaymentRequired object' flow. This is exactly the extra behavioral context annotations cannot carry.

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, front-loaded with the 'Use when' trigger, followed by the payment/pricing caveat. Dense but every clause (captions fallback, translation, non-charging, price, PaymentRequired) carries actionable information. Slightly long as a single run-on first sentence.

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 still characterizes the return shape (full transcript text plus timestamped segments) and covers the failure/payment paths an agent must handle. Nothing material for correct invocation 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 coverage is 100%, so baseline is 3, but the description adds real semantics: language is a preference with manual-captions-first / auto-generated fallback resolution, and translation only applies when the video lacks the requested language. These clarify how lang and translate interact beyond the schema's field-level text.

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+resource outcome: 'full transcript text plus timestamped segments, in the requested language'. An agent immediately knows this returns spoken content rather than metadata. It does not explicitly distinguish itself from siblings like youtube_video or youtube_search, so it falls short of a 5.

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?

'Use when you need what is said in a YouTube video' gives a clear triggering condition, and the caption fallback/translation notes clarify expected behavior. However, no alternative sibling is named as a contrast (e.g. 'for title/description metadata use youtube_video'), so routing between the seven YouTube siblings 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.