get_interest_suggestions

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

With no annotations, the description carries the burden of disclosure. It explains the optional access_token behavior ('will use cached token if not provided'), the default limit, and the exact return structure (JSON string with id, name, audience_size, description). This goes beyond basic expectations, though it omits details about error handling or rate limits.

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 well-structured with clear Args and Returns sections, front-loaded with a one-sentence purpose. Every piece of information is useful and directly actionable, without redundancy.

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?

The description covers all three parameters, the return format, and operational nuances (token caching, default limit). Combined with the output schema, an agent has everything needed to select and invoke the tool 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 has 0% coverage, but the description's Args section thoroughly explains each parameter, including examples for interest_list, the optional nature of access_token, and the default for limit. This fully compensates for the schema gap and adds practical guidance.

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 the tool's function: 'Get interest suggestions based on existing interests.' This uses a specific verb and resource, distinguishing it from siblings like 'search_interests' by emphasizing it operates on a provided list of interests rather than a free-form search.

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 clear context for when to use the tool ('based on existing interests') and implicitly differentiates it from search-like tools. However, it doesn't explicitly state situations to avoid or name alternative tools, so it falls short of full guidance.

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