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

With no annotations, the description carries the full burden. It discloses the output (list of categories and facets) and the need for a category, giving a clear behavioral picture. It does not mention error handling or permissions, but for a read-only tool, this is adequate.

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 that are focused and front-loaded with the primary purpose. Each sentence adds necessary context without redundancy.

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?

Given the tool's simplicity (one param, no output schema), the description covers its purpose, input requirement, and return value. It also provides context about the taxonomy hierarchy, making it self-sufficient.

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 schema only says 'Category to read taxonomy for,' while the description enriches this by listing example top-level categories (furniture, art, etc.) and emphasizing the requirement. That adds practical meaning beyond the schema.

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 clearly states the tool's function with 'Discover how items on 1stDibs are categorized' and specifies it returns next-level categories and facets. It differentiates from sibling tools like search_items and browse_items, which focus on items rather than taxonomy structure.

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?

It establishes a clear use case for exploring taxonomy and requires a category input with 'You need to specify a category.' However, it does not explicitly name alternatives or provide exclusion criteria, so guidance is context-rich but not fully explicit.

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