list_customer_requests

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It discloses pagination behavior, the precise meaning of the cursor parameter, the per_page range and default, and the response envelope structure (results, total_count, next_cursor, next_page_results). It also clarifies that work items are not included, preventing false expectations. This is comprehensive behavioral context.

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 well-structured with a clear one-line summary followed by a brief domain clarification and then organized Args/Returns sections. Every sentence adds value: the alternative-tool note prevents misuse, and the parameter explanations are brief yet precise. No wasted words.

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 complexity (paginated listing with filters and cursor) and the presence of an output schema (which describes the response items), the description provides all necessary context: usage, pagination mechanics, parameter semantics, and response envelope. There are no significant gaps that would impede an agent from correctly selecting and invoking this tool.

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% description coverage, so the description must fully compensate. It explains every parameter: customer_id is a UUID, query filters by name containing text, cursor is the prior response's next_cursor (omit for first page), and per_page has a range of 1-1000 with default 1000. This far exceeds the schema's bare property definitions and gives the agent everything needed to invoke the tool correctly.

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 opens with a specific verb and resource: 'List a customer's requests (paginated).' It further clarifies the domain by defining what a customer request is and explicitly differentiating from list_customer_work_items, which is the correct tool for reading work items. This leaves no ambiguity about the tool's role.

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 explicit when-to-use guidance by stating that work items addressing a customer request are read via list_customer_work_items, not from this endpoint. It also gives clear pagination usage instructions: 'page again while next_page_results is true,' which tells the agent exactly how to iterate through results. This is strong alternative and usage context.

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