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

Goes well beyond the readOnly/idempotent/openWorld annotations by disclosing the return payload shape (title, channel, views, duration, publish date, thumbnail), the 50-video cap, the flat pricing model, that errors are not charged, and the x402 USDC-on-Base payment flow including the PaymentRequired handshake for unpaid calls. This is exactly the auth/payment context an agent needs and cannot get from structured fields.

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?

Front-loads the use case and packs return fields, filters, pricing, and payment mechanics into a compact block with no filler. Sentences are dense and slightly run-on, but nothing is wasted and the most decision-relevant information (paid, $0.002, PaymentRequired) is easy to find.

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 compensates by enumerating returned fields, and it fully covers the non-obvious commercial/payment prerequisites. For a read-only search tool, nothing an agent needs to invoke 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 schema already documents all seven parameters. The description restates three filter categories (sort order, upload date, duration) and the 50-video ceiling but adds no syntax, format, or behavioral nuance beyond the schema, so the baseline 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?

States a specific verb+resource ('find YouTube videos for a query') and adds a use-case framing ('competitor or trend research') that helps an agent recognize the scenario. It does not explicitly name or contrast with siblings like youtube_video or youtube_channel, so an agent must infer that this is query-based discovery rather than ID-based retrieval.

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?

Gives a clear when-to-use trigger ('when you need to find YouTube videos for a query') plus concrete example scenarios. No when-not conditions or named alternatives are provided, so it stops short of full routing guidance.

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