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by uk.co.levtestingcost

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

submit_enquiry

Submits an enquiry to LEV Testing Cost — 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: "Happy for my details to go to relevant LEV testing companies, who'll quote me directly."

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
answersYesthe person's answers, keyed by field key
consentYestrue only when the person has agreed to: Happy for my details to go to relevant LEV testing companies, who'll quote me directly.
confirmationNothe confirmation token from step 1, after the person has approved the summary

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden, and it does so thoroughly. It discloses the two-step validation-and-submit behavior, the requirement that consent is explicit, the email-link click requirement before providers see anything, and the exact consent wording. This gives an agent an accurate model of side effects and sequencing.

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

Conciseness5/5

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

The description is dense but every sentence earns its place: it starts with the core distinction, then gives the two steps, then the consent requirement. The consent phrasing is repeated from the schema, but here it is essential context for the agent's conversation flow, not filler.

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 two-step mutation tool with no output schema and no annotations, the description fully explains the return values at each step (summary, consent line, confirmation token), the expected user interaction, and the final email behavior. It even mentions the non-obvious requirement that the user must click the emailed link before submission is visible to providers. Nothing essential is missing.

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

Parameters5/5

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

Although the schema already documents all three parameters, the description adds critical semantic meaning: 'confirmation' is tied to step 2, 'answers' must be keyed by field keys from enquiry_fields, and 'consent' is tied to a specific consent statement. It explains how the parameters relate across the two calls, going beyond mere field definitions.

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?

The description states a clear verb and resource: 'Submits an enquiry to LEV Testing Cost,' and immediately distinguishes it from a purchase or guaranteed quote. The two-step flow is explicit, making the tool's purpose and scope unambiguous even before considering the input 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?

The description provides exact step-by-step usage: call first with answers and consent=true, review the returned summary and consent line, then call again only if the person agrees, adding the confirmation token. It also says what the tool is NOT for and references 'enquiry_fields' for the answer keys, giving clear routing guidance.

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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TDQS

A4.2/5.0
Disambiguation5/5

Each tool has a clearly distinct role: enquiry_describe explains the workflow and consent, enquiry_fields provides the input schema, and submit_enquiry executes the two-step submission. There is no meaningful overlap that would cause an agent to select the wrong tool.

Naming Consistency3/5

The names are all lowercase and readable, but they follow mixed conventions: enquiry_describe and enquiry_fields use a noun-first prefix while submit_enquiry uses verb-first. A consistent pattern like describe_enquiry, list_enquiry_fields, and submit_enquiry would be cleaner.

Tool Count5/5

Three tools is well-scoped for a single enquiry submission workflow: one explainer, one schema provider, and one action tool. Each tool earns its place without redundancy or unnecessary surface area.

Completeness5/5

The tool set covers the full submission flow: understanding the process, inspecting all required fields, submitting with consent, and confirming with a token. The workflow has no dead ends within its stated scope.

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