list_categories

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns a list of categories with examples ('os', 'lang', etc.), which is useful behavioral context. However, it doesn't mention potential limitations like pagination, rate limits, authentication needs, or error conditions. For a read-only tool with no parameters, this is adequate but not comprehensive.

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 appropriately sized with two sentences: the first states the purpose and output, the second provides usage guidance. It's front-loaded with key information and avoids redundancy. However, the second sentence could be slightly more concise (e.g., 'Use for taxonomy exploration or to help users find related products').

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 (0 parameters, no annotations, no output schema), the description is reasonably complete. It explains what the tool does and provides example outputs, which helps compensate for the missing output schema. However, it lacks details on return format (e.g., list structure, data types) and doesn't address potential edge cases, leaving some gaps for an AI agent.

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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details beyond the schema, but that's appropriate here. Baseline is 4 for 0 parameters, as the description focuses on output semantics instead, which is valuable given the lack of an output 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 purpose: 'Discover how products are organized by category' and 'Returns categories like...' which specifies the verb (discover/return) and resource (categories). It distinguishes from siblings like list_products or get_category_products by focusing on category taxonomy rather than products themselves. However, it doesn't explicitly contrast with all siblings (e.g., list_tags).

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 provides implied usage guidance: 'Use this to understand the taxonomy or to help users explore related products.' This suggests contexts where category exploration is needed. However, it doesn't explicitly state when to use this versus alternatives like get_category_products (which might fetch products within a category) or list_tags (another organizational scheme), nor does it mention any prerequisites or exclusions.

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