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 clearly states that the question is lodged as a ticket, a human answers it, and a ticket ID is returned for polling. This conveys the asynchronous nature and the expected flow. It does not mention side effects like authentication, rate limits, or potential delays, but for a simple request tool, the core behavior is adequately disclosed.

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 two sentences long, front-loaded with the purpose, and contains no filler. It efficiently states what the tool does, the process, and the return value, all without redundancy. Every sentence earns its place.

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 5 parameters, no output schema, and no annotations, the description is fairly complete. It explains the purpose, the asynchronous human-answered flow, and how to follow up via check_rfq_status. It does not address error handling or edge cases, but those are not critical for the core functionality. The description provides enough 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?

Schema description coverage is 100%, meaning every parameter is already documented with a clear description. The tool description adds no additional semantic context beyond what the schema provides, such as usage examples or relationships between parameters. It does not compensate for the high schema coverage with extra insight, so a baseline of 3 is appropriate.

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 states a specific verb ('Ask') and resource (commercial or procedural question), and explicitly describes the outcome (ticket created, human answers, returns ticket ID). It distinguishes itself from siblings by framing the use case as a question rather than a formal submission or status check, which is sufficient for an agent to tell it apart.

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 clearly indicates when to use this tool: for commercial or procedural questions that need a human answer. It also points to the companion tool 'check_rfq_status' for polling, which implies when to use that alternative. However, it does not explicitly state that this is not for formal RFQ submissions (submit_rfq) or escalation (escalate), leaving some ambiguity.

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