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

With no annotations, the description carries full behavioral disclosure. It clearly explains the two-step process, the validation and summary return, the consent line, the confirmation token, the email link that must be clicked before providers see it, and the exact consent text. It also discloses that it is not a purchase and not a guaranteed quote. This is comprehensive transparency.

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 detailed but well-structured, front-loading the critical caveat ('NOT a purchase, NOT a guaranteed quote') and then logically laying out steps 1 and 2. Every sentence serves a purpose, covering the process, the consent text, and the email link requirement without redundancy. It is appropriately sized for the tool's complexity.

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 two-step interaction, consent requirement, and email verification step, the description covers all essential operational details. It explains the return of a summary, consent line, and confirmation token in step 1, and the final submission and email link in step 2. No output schema exists, but the description sufficiently explains the expected returns, making it complete for an agent to use 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 coverage is 100%, and the description adds substantial meaning: it explains answers are keyed by field keys from enquiry_fields, consent must be true only when the person agrees to the specific consent line, and confirmation is the token from step 1 used to finalize. This goes beyond the schema's basic descriptions and clarifies the workflow-dependent semantics.

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 submits an enquiry to Forklift Training Quotes, explicitly distinguishes it from a purchase or guaranteed quote, and describes the two-step flow. It references the specific resource (human providers) and the action (submit), making the purpose unambiguous and differentiated from siblings like enquiry_fields.

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 usage context: step 1 for validation and obtaining a token, step 2 for final submission after consent, and notes the consent requirement. It also indirectly guides the agent to use enquiry_fields for the answers' field keys. However, it does not explicitly name the sibling tools or explain when to use enquiry_describe instead, so it stops short of a 5.

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