Get YouTube search suggestions

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 clearly states this is a 'direct read' on live YouTube search demand, implying no side effects, and describes the iterative chaining behavior. It does not cover rate limits or error cases, but for a simple read-only autocomplete tool, the core behavior is transparent.

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?

Three short sentences each carry distinct value: definition, primary use case, and an advanced chaining pattern. The most identifying trait, 'YouTube's autocomplete', is front-loaded. There is no filler or repetition.

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 one-parameter tool with no output schema, the description conveys enough for an agent to invoke it correctly: the input is a seed term and the result is what users actually type. It could be more explicit about the return format or any authentication/network expectations, but those are minor gaps.

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 the parameter is already documented with a description and examples. The tool description adds keyword-research context but no new syntax, formatting, or constraints beyond the schema. This matches the baseline for high schema coverage.

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 identifies a specific verb and resource: 'YouTube's autocomplete for a seed term'. This clearly differentiates it from siblings like search_videos or get_transcript, since autocomplete suggestions are a distinct data product. The phrasing 'direct read on real search demand' reinforces the exact purpose.

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?

It explicitly tells the agent when to use the tool: for keyword research, seed a niche term, and chain suggestions to map a topic space. It does not mention when not to use it or name specific sibling alternatives, but the given context is clear enough to guide selection.

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