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, and it excels. It reveals that step 1 only validates and returns a summary/consent/token, that submission requires the token, that an email with a clickable link is sent, and that providers see the enquiry only after the link is clicked. It also explains the exact meaning of consent, which is crucial for safe user interaction.

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 longer than average but every sentence earns its place. It front-loads the core purpose and critical exclusions, then organizes the two-step workflow with clear numbering. The exact consent text and email behavior are important details that justify the length, and the structure makes it easy to follow.

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 no annotations and no output schema, this description is remarkably complete. It explains the entire flow from initial call to final submission, including intermediate return values, the required token, and the post-submission email step. An agent receiving this description would be able to invoke the tool correctly at both stages and handle user consent appropriately.

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?

Although schema coverage is 100%, the description adds meaningful semantics beyond the property names. It specifies that 'answers' must be keyed by field keys from enquiry_fields, that 'consent' must be true and match the exact consent text, and that 'confirmation' is the token returned in step 1. This contextual mapping turns the schema's generic descriptions into a usable procedure.

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 clear specific verb and resource: 'Submits an enquiry to Car Import Calculator.' It immediately distinguishes the tool by stating what it is not ('NOT a purchase, NOT a guaranteed quote'), which helps separate it from siblings like calculate and calculator_describe. It also references enquiry_fields for the answer keys, anchoring its role in the broader flow.

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 an explicit two-step procedure: first call with answers and consent=true to get a confirmation token, then call again only after user approval. It clearly states when not to use it ('NOT a purchase, NOT a guaranteed quote') and specifies the consent condition verbatim, leaving no ambiguity about when and how to invoke the tool.

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