get_interest_suggestions

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the optional access_token parameter and caching behavior ('will use cached token if not provided'), which adds useful operational context. However, it doesn't address important behavioral aspects like rate limits, authentication requirements beyond the token, error conditions, or whether this is a read-only operation (though 'Get' implies it).

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 sections (Args, Returns) and uses bullet-like formatting. Each sentence adds value: the purpose statement, parameter explanations, and return format description. It's appropriately sized for a tool with 3 parameters and output documentation, though the formatting could be slightly more polished.

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?

Given the tool has an output schema (though not shown here), the description appropriately documents the return format. With 3 parameters and no annotations, the description provides good coverage of parameter semantics and basic behavioral context. The main gap is the lack of usage guidelines relative to sibling tools, but otherwise it's reasonably complete for a read-oriented suggestion tool.

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. It provides meaningful explanations for all three parameters: clarifies that interest_list contains 'interest names' with an example, explains the optional nature and caching behavior of access_token, and specifies the default value and purpose of limit. This adds substantial value beyond the bare schema, though it doesn't fully document parameter constraints or validation rules.

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 purpose: 'Get interest suggestions based on existing interests.' It specifies the verb ('Get') and resource ('interest suggestions'), and the 'based on existing interests' phrase adds useful context. However, it doesn't explicitly differentiate this from sibling tools like 'search_interests' or 'search_behaviors' that might also find interests.

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 no guidance on when to use this tool versus alternatives. With sibling tools like 'search_interests' and 'search_behaviors' available, there's no indication of when this suggestion-based approach is preferable to direct search methods. The description only explains what the tool does, not when it should be selected.

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