youtube_search_suggestions

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does add key context such as 'No quota cost (uses YouTube's public suggest endpoint)', which is useful. However, it doesn't mention response format, rate limits, or whether the operation is strictly read-only, leaving some gaps for a tool with no annotation support.

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 concise and front-loaded with the main purpose in the first sentence. It includes only relevant details (use case, quota behavior, parameter explanations) without any fluff. The structure is clean and easy to scan.

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?

For a simple two-parameter tool with no output schema and no annotations, the description covers the essential aspects: purpose, use case, quota behavior, and parameter meanings. It does not specify the exact return structure or potential errors, but given the simplicity, it is reasonably complete for an agent to invoke 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?

The schema description coverage is 0%, so the description must compensate. The 'Args' section explains both parameters: query is 'Partial search query to get suggestions for' and language is 'Language code (e.g., "en", "es")'. This adds meaningful semantics beyond the bare property names, though it could be more detailed about language formats or query constraints.

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 'Get YouTube autocomplete/search suggestions for a query' with a specific verb and resource. It distinguishes itself from siblings by explicitly mentioning 'autocomplete/search suggestions' and the SEO keyword research use case, which sets it apart from youtube_search and analytics tools.

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 a clear use case: 'Useful for SEO keyword research — shows what people are searching for.' This implies when to use it, though it does not explicitly name alternatives or state when not to use it. The context is clear enough for an agent to select this tool over siblings.

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