zalando_category

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

With no annotations provided, the description carries the burden of behavioral disclosure. It adds useful context: the tool browses by slug, requires market (no default), returns normalized result cards plus total_count, and slugs are market-specific. However, it does not disclose potential failure modes (e.g., invalid slug), rate limits, or authorization requirements. This is moderate but not comprehensive disclosure.

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 three sentences long and front-loaded with a clear purpose statement ('Browse a Zalando category or brand'). Each subsequent sentence adds distinct and essential information (return format, slug sourcing, market requirement) without repetition or filler. It is appropriately dense and well-structured.

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 tool with only two parameters and no output schema, the description is quite complete. It explains the return type by referencing zalando-search's normalized result cards and the added total_count, provides guidance on obtaining valid slugs, and points to zalando-markets for the country list. Minor gaps remain, such as pagination behavior and error handling, but the description covers the essential context needed for an agent to invoke the tool 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?

The input schema already describes both parameters ('Zalando country storefront' and 'Zalando category or brand URL slug, in the target market's own language'). The description adds value beyond the schema by providing concrete slug examples, explaining that slugs are market-specific with cross-market examples (shoes/chaussures/scarpe), and directing users to zalando-markets for the full storefront list. It also emphasizes that market is required, which is already in the schema but reinforced with rationale.

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 the specific verb 'Browse' and identifies the resource as 'Zalando category or brand listing'. It clearly distinguishes itself from sibling tools by explicitly comparing its output to zalando-search ('returns the same normalized result cards as zalando-search, plus the category's upstream total_count') and by defining the input as a URL slug. Examples of slugs (shoes, womens-dresses) further clarify the resource type.

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 on when to use this tool: when you have a category or brand slug, with guidance that slugs are market-specific and should be taken from the market's own site navigation or a product's url field. It references the alternative zalando-search and points to zalando-markets for the storefront list. However, it stops short of explicitly stating when NOT to use it (e.g., when performing a free-text search), so it lacks the full when/when-not contrast.

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