recommend_style

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

With no annotations provided, the description carries the full burden. It explicitly states 'No AI inference — uses deterministic scoring against style characteristics', which clarifies the computational behavior and lack of AI stochasticity. It does not detail auth needs or rate limits but is adequate for a read-only recommendation tool.

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?

Two concise sentences: first states the purpose, second adds critical behavioral info (deterministic, returns reasoning and alternatives). No wasted words, front-loaded with core action.

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 4 parameters (2 required), no output schema, and no annotations, the description adequately explains inputs and output (top match with reasoning and alternatives). It could elaborate on the return structure or examples, but is sufficiently complete for an agent to understand the tool's function.

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 description coverage is 100%, and the description does not add meaning beyond what the schema already provides. The examples in the description are similar to the schema's description, so no additional value is added. Baseline of 3 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 it 'recommends a design style' based on brand, objective, and demographic. It also distinguishes itself from the sibling tool 'get_style' by specifying it returns a top match with reasoning and alternatives, and clarifies it uses deterministic scoring versus AI inference.

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 recommending a style based on inputs, but does not explicitly state when to use it versus alternatives like 'get_style'. There is no guidance on when not to use it or specific prerequisites.

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