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

No annotations are provided, so the description carries the full burden and meets it: it discloses validation behavior, what Step 1 returns (summary, consent line, token), the required human approval gate, and the post-submission email-link verification before any provider sees the data. It even reproduces the exact consent meaning. This is unusually rich behavioral context for a mutation tool.

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?

Long, but every sentence earns its place for a two-step, human-consent gated flow, and it is front-loaded with the 'not a purchase' disambiguation before the step detail. Slightly verbose in restating the consent text twice, but justified by the consent requirement.

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?

There is no output schema, and the description compensates by describing exactly what Step 1 returns and what happens after Step 2 (email link the person must click). Combined with the nested-object answers parameter, an agent has everything needed to drive the flow 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%, so the baseline is 3, but the description adds real meaning: 'answers' is keyed by field key from enquiry_fields, 'consent=true' is tied to specific language the person must have agreed to, and 'confirmation' is the token from Step 1 used only after approval. This goes beyond the schema's field-level wording.

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?

States a specific verb and resource ('submits an enquiry'), names the target ('Arizona Roof Replacement Cost'), and immediately disambiguates with 'NOT a purchase, NOT a guaranteed quote.' An agent can distinguish this from the sibling discovery tools (enquiry_describe, enquiry_fields) without opening a schema.

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?

Gives an explicit two-step protocol: Step 1 with answers+consent=true, show the person the summary and consent line; Step 2 'only if the person agrees' with the token. The condition that selects each call is spelled out, leaving nothing to inference.

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