get_recommendations

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It only states the action and provides no context about behavior for invalid/missing userId, authentication requirements, pagination, or response shape. The 'Get' verb implies a read operation but doesn't confirm non-destructiveness or edge cases.

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, concise sentence that front-loads the core purpose and includes useful examples in parentheses. No wasted words or redundant information.

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 simple tool with two optional parameters and no output schema, the description is adequate but leaves gaps around response format, what 'personalized' means operationally, and behavior when no userId is provided. It covers the primary purpose but lacks depth needed for full self-service understanding.

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 already fully describes both parameters (lang and userId) with 100% coverage. The description adds only a minor implication that userId drives personalization, but doesn't provide any additional syntax, format, or edge-case semantics beyond what the schema states. Baseline 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 uses a specific verb ('Get') and clearly identifies the resource ('personalized product recommendations'), with parenthetical examples ('Recommended for You, Trending, New Arrivals') that further clarify scope. This distinguishes it from siblings like search_products (search vs recommend) and get_similar_products (product-based vs customer-based).

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 phrase 'for a customer' and the category examples imply this tool is for recommendation surfaces, but there is no explicit guidance on when to use it versus alternatives like search_products or customer_search_products. No when-not or exclusion conditions are stated.

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