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Glama

OKC HVAC Calculator | Repair or Replace Decision Tool

submit_covington_booking_request

Submit a booking (appointment) request to Covington Heat & Air. Requires an API key and explicit user consent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
emailNo
notesNo
phoneYes
cityZipNo
consentYes
consentTextNo
serviceTypeNo
preferredTimeNo

Schema Changelog

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

  1. First observed

TDQS

C2.9/5.0
Behavior3/5

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

With no annotations, the description carries the disclosure burden. It usefully discloses that an API key and explicit consent are required, which is relevant behavioral context for a submission tool. But it does not explain side effects, irreversibility, failure behavior, or what happens after the request is submitted, so the transparency is only partial.

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 a single dense sentence that front-loads the action and target, then adds the two critical prerequisites. There is no filler and every word contributes.

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

Completeness2/5

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

For a tool with nine parameters, zero schema descriptions, no annotations, and no output schema, this description is not complete enough for reliable invocation. It does not specify parameter formats, allowed service types, consentText semantics, preferredTime syntax, or response/confirmation behavior; it only establishes the basic purpose and key prerequisites.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description adds no meaning for any of the nine parameters. It only implies consent is required, leaving fields like serviceType, cityZip, consentText, and preferredTime entirely unexplained. The description does not compensate for the lack of schema-level documentation.

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 the action (submit a booking/appointment request), the target (Covington Heat & Air), and the appointment framing distinguishes it from the sibling lead-request tool. However, it does not explicitly call out the sibling or say 'use this for bookings, not leads,' so it stops just short of full differentiation.

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

Usage Guidelines2/5

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

The description gives prerequisites ('requires an API key and explicit user consent') but no guidance on when to use this tool versus submit_covington_lead_request or the other HVAC tools. There are no when-to-use, when-not-to-use, or alternative-selection instructions.

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

A3.8/5.0
Disambiguation5/5

Each tool targets a distinct action or resource: retrieving articles, searching articles, getting business info, checking service area, describing the analysis tool, running the analysis, and submitting two different types of contact requests. The two content tools are clearly separated as search vs. full retrieval, and booking vs. lead submissions are differentiated by their descriptions.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern with snake_case: get_*, search_*, run_*, and submit_*. While the domain prefixes vary (hvac, okc_hvac, covington, repair_or_replace), the overall grammatical structure is uniform and predictable.

Tool Count5/5

Eight tools is well-scoped for this server's purpose. It covers content discovery, business information, service area verification, decision tool metadata, the actual analysis, and two conversion paths without unnecessary redundancy.

Completeness5/5

The tool surface covers the full user journey: learning through articles, verifying eligibility through service area, running the repair-or-replace analysis, and taking action via booking or lead submission. For a read-mostly decision tool and lead generation server, there are no meaningful dead ends.

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