everlane_product

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

No annotations, so description carries the burden. It discloses normalized output and fixed server-side URL, adding useful context beyond annotations. However, it doesn't mention failure behavior, auth, or rate limits, and the single-param call has limited behavioral surface.

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 sentences, each meaningful: what it returns, normalization, and handle clarification. No fluff; front-loads the 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?

For a single-param read tool with no output schema, this is nearly complete. It explains what handle means and where it comes from. The only gap is not describing what normalized product detail includes, but no output schema means return fields are somewhat expected from surrounding structure.

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%, and the description adds value by clarifying that handle is a URL slug from everlane.com. With full schema coverage, baseline is 3, and the slug clarification earns a 4.

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 specifies it gets a single Everlane product by handle, distinguishes it from product list/search tools, and mentions normalization. It doesn't explicitly name sibling alternatives for disambiguation.

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?

Clear context: use when fetching one specific product by URL slug. The storefront URL being fixed server-side helps, but no explicit guidance on when to prefer related tools like everlane_products or everlane_collection_products.

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