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Party Wall Quotes: the site's own MCP server — enquiry (enquiry = a human handoff, not a...

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Status
Healthy
Uptime
99.7% over 41 days
Last Tested
Transport
Streamable HTTP · MCP 2025-11-25
URL

TDQS

A4.1/5.0

Scored across 3 tools

Disambiguation5/5

Each tool has a clearly distinct purpose: enquiry_describe explains the process, enquiry_fields lists form fields, and submit_enquiry submits the enquiry. The descriptions emphasize when to use each, so there is no ambiguity.

Naming Consistency4/5

All tools use a consistent 'enquiry_' prefix followed by a verb or noun (describe, fields, submit). This is mostly consistent, though mixing verbs and nouns slightly reduces predictability.

Tool Count3/5

With only 3 tools, the count is borderline low for the apparent scope, which includes understanding, field discovery, and submission. However, each tool serves a distinct and necessary role in the flow.

Completeness4/5

The toolset covers the essential lifecycle of an enquiry: explanation, field listing, and submission. However, it lacks tools for checking status, retrieving an enquiry, or canceling, which could be useful for a complete experience.

Available Tools

3 tools
enquiry_describeWhat you get: an ENQUIRY with a human (not a purchase, not a guaranteed quote)AInspect

Read first. States plainly what submit_enquiry does on Party Wall Quotes: it starts an enquiry with human providers who quote directly. Nothing is bought, ordered or paid; no quote is guaranteed; it is free. Also returns who receives the details, the consent wording, and how the person confirms.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure and does so well: it states that nothing is bought, ordered, or paid, that no quote is guaranteed, and that it is free. It also discloses what the returned content includes, such as who receives the details and the consent wording. It stops short of explicitly saying the tool itself performs no mutations, but the explanatory framing makes this reasonably clear.

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 compact and front-loaded with the most important guidance, 'Read first.' Every sentence adds value: what the enquiry is, what it is not, and what the returned description contains. There is no filler or redundant repetition.

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 no-parameter describe tool with no output schema, the description is complete enough for an agent to understand what it returns and why it matters. It names the core product behavior, the key exclusions (no purchase, no guarantee), and the specific return elements, so an agent can correctly choose and invoke the tool.

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 tool takes zero parameters and the schema is empty with full coverage, so parameter-level documentation is unnecessary. The description appropriately focuses on behavior and return content rather than parameters, leaving no semantic gap.

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

Purpose4/5

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

The description clearly states that enquiry_describe explains what submit_enquiry does on Party Wall Quotes, including that it starts an enquiry with human providers. It distinguishes itself from submit_enquiry by being the 'read first' explanatory tool, though it does not explicitly address how it differs from enquiry_fields.

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

Usage Guidelines4/5

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

The opening directive 'Read first' clearly signals that this tool should be used before submit_enquiry, and the description frames it as the plain-language explanation of that sibling tool. It provides clear context for when to use it, though it does not mention exclusions or alternatives beyond the implicit distinction from the other siblings.

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

enquiry_fieldsThe questions the enquiry asksAInspect

Every field of the Party Wall Quotes enquiry: key, label, type, whether required, help text and the allowed options where there are any. Pass answers to submit_enquiry keyed by field key.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A3.9/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It does this well by specifying exactly what information is returned and its scope ('Every field'). As a non-mutating metadata/introspection tool, side effects are unlikely, and nothing in the description suggests otherwise.

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 compact and front-loaded: the first sentence defines the tool's scope and output content, while the second sentence provides actionable usage guidance. No words are wasted.

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

Completeness4/5

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

For a zero-parameter, no-output-schema tool, the description covers the key facts: what fields are returned and how those field keys connect to submit_enquiry. It does not explicitly position itself against enquiry_describe, but the field-specific content is sufficient for an agent to make a correct selection.

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 tool has zero parameters, so there is no parameter documentation burden; the baseline of 4 applies. The description adds useful cross-tool context by clarifying that the field keys returned here are the same keys to use when calling submit_enquiry.

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

Purpose4/5

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

The description clearly identifies the resource ('every field of the Party Wall Quotes enquiry') and enumerates the exact attributes returned: key, label, type, required, help text, and options. It lacks an explicit action verb like 'Returns' or 'Lists,' and it does not directly distinguish itself from enquiry_describe, though the field-level scope is apparent.

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

Usage Guidelines3/5

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

The instruction to pass answers to submit_enquiry keyed by field key implies this tool is useful for discovering the fields needed for submission. However, it never explicitly states when to use this tool versus enquiry_describe or provide exclusion criteria, so usage guidance remains mostly inferred.

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

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

Submits an enquiry to Party Wall Quotes — 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: "Send my contact details to up to three building and structural surveyors, chosen by Party Wall Quotes, who'll contact me directly. I'll be emailed each firm's name as my details go to it, and can stop any more firms getting them."

ParametersJSON Schema
NameRequiredDescriptionDefault
answersYesthe person's answers, keyed by field key
consentYestrue only when the person has agreed to: Send my contact details to up to three building and structural surveyors, chosen by Party Wall Quotes, who'll contact me directly. I'll be emailed each firm's name as my details go to it, and can stop any more firms getting them.
confirmationNothe confirmation token from step 1, after the person has approved the summary

TDQS

A4.8/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and does so: it discloses validation on step 1, the returned summary/consent line/token, that the enquiry is not visible to providers until the person clicks an email link, and exactly what consent attests to. These are non-obvious side effects an agent must know before invoking.

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?

Well front-loaded: the negation of purchase/quote comes first, then the numbered steps. It is long, and the consent sentence is duplicated verbatim from the schema, which is slightly wasteful, but nearly every clause conveys operational guidance.

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-phase, stateful submission tool with a nested answers object and no output schema, the description covers inputs, the token round-trip, the consent semantics and the post-submission email gate. An agent has everything needed to call it correctly.

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 the baseline is 3, but the description goes further by explaining that answers are keyed by field key from enquiry_fields and that the confirmation token originates from step 1. It clarifies inter-parameter workflow rather than just restating types.

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?

States a specific verb and resource ('Submits an enquiry') and immediately disambiguates what it is not ('NOT a purchase, NOT a guaranteed quote'). The sibling tools (enquiry_describe, enquiry_fields) are data-lookup helpers, and this description makes clear this is the terminal submission action.

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?

Gives an explicit two-step protocol: step 1 with answers and consent=true, then step 2 only after the person approves, with the confirmation token. The condition gating step 2 ('only if the person agrees') is stated outright, 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.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool update
    • Changedsubmit_enquiry1 field changed
      • changedInput schema / properties / consent / description
        Previous value: -"true only when the person has agreed to: Happy for my details to go to relevant local party wall surveyors, who'll quote me directly."New value: +"true only when the person has agreed to: Send my contact details to up to three building and structural surveyors, chosen by Party Wall Quotes, who'll contact me directly. I'll be emailed each firm's name as my details go to it, and can stop any more firms getting them."
  2. 3 tool updates
    • First observedenquiry_describe
    • First observedenquiry_fields
    • First observedsubmit_enquiry

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