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by uk.co.whichevcharger

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

submit_enquiry

Submits an enquiry to Which EV Charger — 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 local EV charger installers, who'll contact 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 local EV charger installers, who'll contact 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

A4.9/5.0
Behavior5/5

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

With no annotations present, the description carries the full disclosure burden and meets it: it explains validation before submission, the returned summary/consent/token, the required consent line, and the post-submission email-link requirement. It also clarifies that no provider sees the enquiry until the person clicks the link.

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 longer than average but every sentence earns its place: the non-purchase disclaimer is front-loaded, and the two steps are clearly numbered. The consent line is repeated verbatim, which removes ambiguity about what consent means.

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 consent-sensitive two-step submission with no annotations and no output schema, this description gives enough guidance to call the tool correctly end-to-end. It covers prerequisites, the two call phases, the consent text, and the delivery/visibility outcome; missing error-handling details are not essential for correct invocation.

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?

The schema already describes all three parameters (100% coverage), so the baseline is 3; the description adds useful sequencing by tying 'confirmation' to the step-1 return value and 'answers' to enquiry_fields. It does not exhaustively redefine the parameter types, but it gives the agent the workflow context needed to populate them correctly.

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 names a specific action ('submits an enquiry') and a specific target ('Which EV Charger', human providers), and explicitly disambiguates from a purchase or guaranteed quote. This separates it from the sibling enquiry_describe/enquiry_fields tools by outcome, so an agent knows what this tool is for.

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?

It provides a precise two-step invocation protocol, states the condition for proceeding to step 2 ('only if the person agrees'), and gives a when-not boundary ('NOT a purchase, NOT a guaranteed quote'). It also points to enquiry_fields as the source of answer keys, giving the agent the surrounding workflow context.

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

A3.7/5.0
Disambiguation4/5

The checker tools and enquiry tools form two clear groups, and within each group purposes are mostly distinct. One minor overlap exists: checker_answer returns the next question for a choice while checker_tree already contains the full decision graph, so an agent could use either to reason ahead.

Naming Consistency4/5

The checker_ and enquiry_ prefixes make tool groups easily recognizable, and overall naming is readable. It is not perfectly uniform because checker_answer and checker_tree are noun-like while checker_start and submit_enquiry are verb-like, but the pattern is still predictable.

Tool Count5/5

Six tools is well-scoped for this server: three cover the interactive decision guide and three cover the enquiry submission flow. Each tool serves a necessary role, and the count feels neither thin nor bloated.

Completeness5/5

The checker workflow is fully covered with start, answer, and full tree access, and the enquiry workflow is covered with descriptions, fields, and a two-step submission process. There are no obvious missing operations for the apparent scope of the server.

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