get_interest

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

Without annotations, the description carries full burden. It explains the composite scoring and tiers but does not disclose whether the operation is read-only, any rate limits, or behavioral traits beyond what is stated. The presence of an output schema reduces need for return format details, but more behavioral context (e.g., 'read-only aggregation') would improve clarity.

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: two main sentences plus a tier list. Every sentence adds meaningful information 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?

For a tool with no parameters and a simple output (tiers with explanation), the description is complete. It explains the concept, signals, and ranking tiers. The presence of an output schema obviates need for return format details.

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 input schema has no parameters; schema coverage is complete. The description adds value by explaining what the tool does, which is sufficient given zero parameters. Baseline 4 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?

The description clearly states the tool retrieves term interest scores as composite rankings, with specific signals and tier names, distinguishing it from other term-related tools like lookup_term or random_term.

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 implies usage for obtaining interest rankings but does not explicitly indicate when to use this tool versus alternatives (e.g., lookup_term for term details, propose_term for suggestions). No 'when not to use' guidance is provided.

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