Search YouTube

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

Annotations already declare openWorldHint=true and readOnlyHint=false, but the description adds genuine behavioral value beyond them: the result ordering ('ranked by views'), the exact credit cost ('spends about a credit'), and the returned field shape. The credit-cost disclosure is especially useful for an agent managing a budget.

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?

A single front-loaded sentence with zero filler; the core purpose leads, followed by use case, return shape, and cost. Every clause earns its place.

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 the returned fields ({desc, author, handle, plays, link, cover}) and the ordering. Combined with the cost note, an agent has everything needed to call and interpret it.

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% with only two params, so the schema fully documents query and limit. The description adds nothing param-specific (e.g. no note on how limit interacts with the credit cost or ranking). 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?

States a specific verb and resource ('Organic YouTube keyword search') plus the backing endpoint (/v1/youtube/search), which cleanly distinguishes it from siblings like search_tiktok, search_instagram and search_reddit. An agent knows exactly which corpus this hits.

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?

Provides a use case ('videos to mine for hooks/angles/long-form structure'), giving clear context for when to reach for it. It stops short of naming alternatives or stating when NOT to use it (e.g. vs find_creators or search_reddit), so it doesn't reach 5.

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