get_preferences

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 indicates this is a read operation ('Get'), but doesn't specify authentication needs, rate limits, error conditions, or the return format. The description is minimal and lacks details on how the data is structured or any constraints.

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 a single, well-structured sentence that efficiently communicates the tool's purpose and scope. It front-loads the key action ('Get your current dietary preferences') and lists specific data fields without redundancy, making it highly concise and easy to parse.

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's simplicity (0 parameters, no annotations, no output schema), the description is adequate but minimal. It covers the basic purpose and data fields, but for a tool with no structured behavioral hints, it could benefit from more context on authentication, return format, or error handling to be fully complete.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately adds no parameter details, focusing instead on the data retrieved. This meets the baseline for tools with no parameters, as it doesn't introduce unnecessary complexity.

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 with a specific verb ('Get') and resource ('your current dietary preferences'), listing the specific data fields retrieved (vegetarian settings, allergens, cuisine types, family-friendly options). It distinguishes from siblings like 'update_preferences' (modification) and 'get_menu' (different resource), though it doesn't explicitly name alternatives.

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 context by specifying 'your current dietary preferences,' suggesting it's for retrieving user-specific settings rather than general data. However, it lacks explicit guidance on when to use this versus alternatives like 'get_menu' or 'get_past_orders,' and doesn't mention prerequisites or exclusions.

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