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

submit_enquiry

Submits an enquiry to Steel Beam Checker — 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 a structural engineer, 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 a structural engineer, 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

A4.6/5.0
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 it discloses key behavior: the first call only validates and returns a token; the second call actually submits; the person must click an email link before any provider sees the enquiry. It also states the exact consent text and that no guaranteed quote is given. This is rich, honest behavioral disclosure.

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 front-loaded with the core purpose and the 'not a purchase' caveat, then follows a numbered Step 1/Step 2 structure. Every sentence carries necessary information, including the exact consent quote, with no filler. The length is justified by the two-step process.

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?

The tool has no output schema or annotations, so the description must cover return values and side effects. It clearly describes the step 1 response (summary, consent line, token) and the step 2 outcome (submission and email link). It doesn't specify step 2's response payload or error cases, but covers the essential flow for an agent to call both steps 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%, giving baseline 3, but the description adds workflow-level semantics: answers are keyed by field key from enquiry_fields, consent must be true per the exact phrasing, and confirmation is the token returned in step 1. This connects each parameter to its role in the two-step flow, exceeding the baseline.

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 opens with 'Submits an enquiry to Steel Beam Checker' — a specific verb, resource, and system. It explicitly distinguishes this from purchases and guaranteed quotes, and states the two-step nature up front. This cleanly separates it from siblings like enquiry_fields and checker_answer.

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 description gives a precise two-step protocol: call with answers and consent=true, show the summary and consent line, then call again with the confirmation token only if the person agrees. It instructs that answers must be keyed by field key from enquiry_fields, pointing to the sibling tool for key discovery. It tells when NOT to use (not a purchase/quote) but doesn't enumerate alternative tools for other actions.

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

A4/5.0
Disambiguation5/5

The checker tools split cleanly into start (entry point), answer (interactive step), and tree (full graph), while the enquiry tools cover explanation, schema, and submission. An agent can easily select based on whether it needs the first question, the next question, the whole guide, or enquiry metadata/action.

Naming Consistency4/5

Names are all lowercase snake_case and mostly use a domain-prefixed pattern: checker_start, checker_answer, checker_tree, enquiry_describe, enquiry_fields. submit_enquiry breaks the order by putting the verb first, and a couple of names are resources rather than actions, so it is not perfectly uniform.

Tool Count5/5

With six tools covering the two distinct workflows (decision guide and enquiry submission), the surface is compact and focused. Each tool has a clear role, and none feel redundant or missing.

Completeness5/5

The decision guide is fully navigable via start/answer, with the full tree available for end-to-end reasoning. The enquiry flow covers explainer, field schema, validation, consent, confirmation token, and final submission, leaving no obvious dead ends.

Resources