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 implies a safe read-only operation but does not explicitly state that it is non-destructive or mention any limitations (e.g., no pagination, no auth requirements). The description is adequate but lacks explicit behavioral guarantees.

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 extremely concise: one sentence for purpose and one for usage guidelines. It is front-loaded with the key action, and every word serves a purpose. No unnecessary text.

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 (1 boolean parameter, output schema exists, sibling tools are related), the description covers the essential scenarios. It explains when to use it relative to filtering or counting. However, it could briefly mention the optional count parameter to be fully complete, but overall it is well-contextualized.

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 one optional boolean parameter 'with_counts' (default false), but the description does not mention it at all. With 0% schema description coverage, the description fails to inform the agent about the ability to include counts. This is a significant omission for a single parameter tool.

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: 'List the distinct customer-service categories in the dataset' with concrete examples (e.g., refund, shipping). It distinguishes from siblings like list_intents which list different entities.

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 explicitly advises when to use this tool: 'Use this first when the user asks what categories exist or when you need to confirm a valid category name before filtering or counting.' This gives clear context and directs the agent to use it as a prerequisite for other operations.

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