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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 FindAgency HQ: 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. Added

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description carries the transparency burden and does useful work: it states that this tool 'states plainly what submit_enquiry does' rather than performing a submission, and it discloses key behavioral facts—nothing is bought/paid, no quote is guaranteed, it is free. It also describes what the tool returns, though it does not explicitly say the tool itself has no side effects.

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?

Four tight sentences, front-loaded with the most important directive ('Read first'), and every sentence adds a distinct fact. There is no filler or redundant explanation beyond what is needed for the tool to stand alone.

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?

Given zero parameters, no output schema, and no annotations, the description supplies the essential context: what the underlying submit_enquiry does, what the enquiry is not, and what information the tool returns. An agent has enough to invoke it correctly without missing critical context.

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 input schema has zero properties, so the baseline 4 applies; there are no parameter semantics for the description to add. The description does not claim or imply parameters, so there is no gap.

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 immediately identifies the tool as the plain-language explanation of submit_enquiry, naming the action ('starts an enquiry with human providers who quote directly'), the platform (FindAgency HQ), and what it is not ('nothing is bought, ordered or paid'). This clearly separates it from the sibling submit_enquiry tool while being specific about its own role.

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' explicitly instructs the agent to consult this description before acting, and the framing makes it clear this is the prerequisite for understanding what submit_enquiry does. It does not explicitly mention alternatives or exclusions, but the relationship to submit_enquiry is unambiguous.

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

A3.9/5.0
Disambiguation4/5

The dataset_* tools are mostly distinct (columns vs provenance vs row vs search vs stats vs top vs compare), though dataset_row, dataset_search, and dataset_compare have overlapping filtering semantics. The enquiry_* tools are clearly distinct. Overall, descriptions clarify confusion, but minor ambiguity exists.

Naming Consistency5/5

All tools follow a consistent lowercase_with_underscores naming convention, with a clear prefix (dataset_ or enquiry_/submit_). The pattern is predictable and uniform across the set.

Tool Count5/5

10 tools is a well-scoped number for a dataset querying and enquiry submission server. Each tool serves a distinct purpose without unnecessary bloat or redundancy.

Completeness4/5

The dataset tools cover the essential read-only operations (columns, provenance, row, search, stats, top, compare) and the enquiry tools cover the full submission flow (describe, fields, submit). Minor gaps exist like no update/cancel for enquiries, but these are not core to the server's stated purpose.

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