farfetch_product

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

No annotations are provided, so the description carries the burden. It discloses that the data is public and sourced from Farfetch's own product pages, which is useful context. However, it doesn't disclose behavioral traits like whether the tool performs any filtering, pagination, rate limits, or what happens when a product is unavailable. The description is honest but doesn't go beyond the basic read operation implied by 'Returns'.

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 two sentences with no wasted words. The first sentence front-loads the core purpose and return fields, and the second sentence adds the data source context. Every sentence earns its place.

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 read-only product detail tool with 2 well-documented parameters and no output schema, the description is largely complete. It lists the return fields, explains the slug's origin, and notes the data source. The only minor gap is that it doesn't mention what happens if the product is not found or if the slug is invalid, but this is a minor omission for a simple lookup tool.

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%, so the schema already documents both parameters. The description adds a small amount of context by explaining that the slug comes from a search result's id field, which helps the agent understand the parameter's origin. However, it doesn't add much beyond the schema's own descriptions, so the 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 states a specific verb ('Returns'), a specific resource ('Farfetch product's full detail'), and enumerates the exact fields returned (name, brand, color, description, images, category breadcrumb, size variants with price and availability). It also distinguishes itself from search tools by noting it returns full detail from product pages. This clearly differentiates it from siblings like farfetch_search, farfetch_categories, and farfetch_designers.

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: it's for retrieving full product details, and the slug parameter is described as coming from a search result's id field, which tells the agent when to use this tool (after a search). However, it doesn't explicitly state when not to use it or name alternative tools like farfetch_search for discovery. The context is clear but exclusions are not stated.

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