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What you get: an ENQUIRY with a human (not a purchase, not a guaranteed quote)

enquiry_describe

Read first. States plainly what submit_enquiry does on Holiday Pay Calculator NZ: 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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the burden of disclosing behavior. It states the tool 'returns who receives the details, the consent wording, and how the person confirms', indicating an informational, read-only output. It also clarifies that the subject process involves no payment or purchase. However, it never explicitly says 'this tool does not submit an enquiry or modify anything', so the side-effect profile is inferred rather than stated.

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?

The description is a clear, front-loaded paragraph that begins with the imperative 'Read first', then explains the tool's purpose and contents. It avoids redundant structured-field repetition and earns its sentences by adding context about the enquiry process and return values. The only minor issue is a slightly dense middle section listing what is not guaranteed.

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 is functionally complete: it specifies the tool's purpose and what it returns (recipient details, consent wording, confirmation process). It provides enough context to set expectations, though it doesn't mention error behavior or whether the output is static text. Overall, nothing essential is missing for safe selection and 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 tool has zero parameters and an empty input schema, so there are no parameter semantics to explain. The description appropriately avoids discussing arguments and focuses on the tool's output. This matches the baseline for a no-parameter tool.

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 explicitly states that the tool 'states plainly what submit_enquiry does', making its role as a descriptive/explainer tool clear. It distinguishes itself from submit_enquiry by specifying that nothing is bought, ordered, or paid and it is free, and from calculator_describe by focusing on the Holiday Pay Calculator enquiry workflow.

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 'Read first' is an explicit cue to consult this tool before taking action, implying it should be used ahead of submit_enquiry. It sets expectations about what the enquiry process entails (human providers, no guaranteed quote, free) but does not name or contrast other sibling tools like enquiry_fields, leaving some routing 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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