gucci_size_guide

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

With no annotations, the description carries the full burden, and it handles this well. It discloses the return format, the non-error behavior for one-size accessories (available: false with no headers/rows), and the fact that absence of a chart is a well-formed signal. It stops short of describing invalid style_code behavior or exact response field names, leaving a minor gap.

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 tightly packed sentences cover purpose, output format, edge-case behavior, and parameter provenance without repetition or filler. Each sentence earns its place, and the opening 'Gucci product size chart' front-loads the core purpose.

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 one-parameter tool with no output schema, the description covers the essential context: what is returned, the format, the edge case for accessory-only styles, and where the style_code comes from. Slightly more detail on the successful response structure (e.g., field names for the headers/rows) would make it fully complete, but it is already sufficient for a correct invocation.

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, but the description adds meaningful provenance: 'style_code comes from gucci-search's or gucci-category's own style_code field.' This tells an agent where to source the parameter, which is more than the schema's bare 'Product style code' provides, justifying 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 names a specific verb and resource: 'Returns Gucci's own size-conversion chart for one product style.' It also describes the output shape ('plain header row plus data rows') and distinguishes this from related Gucci tools by scoping it to size charts and referencing the style_code from gucci-search/gucci-category. This makes the tool's purpose unambiguous and distinct from siblings.

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 context for when to use this tool: after obtaining a style_code from gucci-search or gucci-category. It explicitly states the edge case where a style has no chart and how that is signaled (available: false), which helps an agent decide whether the tool is appropriate. It does not explicitly list excluded alternatives, but the parameter provenance guidance effectively frames usage.

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