fashionnova_product_recommendations

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

No annotations are present, so the description carries the behavioral disclosure burden. It adds useful implementation details: results are normalized, the handle is resolved to a Shopify product id before fetching, and the storefront URL is fixed server-side. However, it does not disclose response shape, error behavior, or other operational traits, leaving room above the minimum.

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?

Three short sentences, with the core purpose front-loaded in the first sentence. Each additional sentence adds relevant implementation context without padding or repetition.

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 single-handle recommendation lookup, the description covers what the tool does, the required input, and important server-side routing behavior. The lack of an output schema and any return-shape details is the main gap, but 'normalized recommended products' gives enough orientation for an agent to invoke it correctly.

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 coverage is 100%, so the baseline is 3. The description adds some meaning for the handle parameter by explaining that it is a route handle resolved server-side to a Shopify product id, but limit and intent are left to the schema descriptions.

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 leads with a specific verb and resource: 'List Fashion Nova product recommendations' for a single product handle. It also differentiates itself from sibling tools like fashionnova_product and fashionnova_products by focusing specifically on normalized recommendations rather than product details or full product listings.

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 gives clear usage context: this tool is for fetching recommendations for one Fashion Nova product handle. It does not explicitly name alternatives or state when not to use it, so it stops short of a 5.

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