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Submit an ENQUIRY to human providers (two steps; not a purchase)

submit_enquiry

Submits an enquiry to Buffrota — NOT a purchase, NOT a guaranteed quote. Step 1: call with the answers (keyed by field key from enquiry_fields) and consent=true; it validates and returns a summary, the consent line and a confirmation token — show the person the summary and the consent line. Step 2: only if the person agrees, call again with the same answers, consent=true and the confirmation token; the enquiry is then submitted, and the person receives an email with a link they must click before any provider sees it. Consent means the person has read and agreed to: "By submitting you agree Buffrota shares your details with commercial cleaning contractors who may contact you."

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
answersYesthe person's answers, keyed by field key
consentYestrue only when the person has agreed to: By submitting you agree Buffrota shares your details with commercial cleaning contractors who may contact you.
confirmationNothe confirmation token from step 1, after the person has approved the summary

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does so substantially: it discloses a two-step state machine, that step 1 only validates and returns a summary/consent line/token, that step 2 triggers an email gate the person must click before providers see it, and the exact consent semantics. It omits failure/validation-error behavior and token expiry, which keeps it from a 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the critical negation, then the two steps in order. The repeated consent sentence and embedded legal quote make it longer than strictly necessary, but each element serves the multi-step flow.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex two-step, nested-object tool with no output schema and no annotations, the description covers the flow, the intermediate return values, the email-verification gate, and consent meaning. Nothing an agent needs to invoke it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3, but the description adds genuine meaning: 'answers' are keyed by field key from enquiry_fields (cross-tool linkage) and 'confirmation' is the token returned by step 1 rather than an arbitrary value. This clarifies how the three params interlock across calls.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a specific verb+resource ('Submits an enquiry to Buffrota') and immediately disambiguates scope with 'NOT a purchase, NOT a guaranteed quote', which separates it from sibling enquiry_describe/enquiry_fields discovery tools. An agent knows exactly what this tool produces without opening the schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly prescribes when to call: Step 1 with answers+consent to validate, Step 2 'only if the person agrees' with the token. It names the precondition (human approval) and the ordering, 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.

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