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OKC HVAC Calculator | Repair or Replace Decision Tool

get_okc_hvac_business_info

Get business information for the OKC HVAC Calculator, powered by Covington Heat & Air (name, phone, email, website, service area).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full disclosure burden. The verb 'Get' and the enumerated fields make clear this is a read-only look-up with a predictable payload, which is adequate for a zero-parameter tool, but it adds no context beyond that (e.g., whether the data is static, whether any external call is made, or response formatting).

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?

A single sentence that is front-loaded with the verb and resource, with the parenthetical field list adding concrete value. Every word earns its place; the provenance note 'powered by Covington Heat & Air' clarifies the data source without bloat.

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 tool with no output schema and no annotations, the description is largely sufficient: it tells the agent exactly which data fields come back, partially substituting for a return-value schema. The only real gap is the unaddressed relationship with get_okc_hvac_service_area, which is minor for such a simple getter.

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 the empty schema fully covers the input side and the rubric baseline for 0 params is 4. The field list in the description concerns the return payload rather than parameters, so no parameter explanation is needed or missing.

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?

States a specific verb and resource — 'Get business information for the OKC HVAC Calculator' — and enumerates the return fields (name, phone, email, website, service area), so the agent knows exactly what it produces. It does not explicitly differentiate itself from the sibling get_okc_hvac_service_area, which overlaps on the service-area field, so it stops just short of a 5.

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?

No guidance on when to use this tool versus the closely related get_okc_hvac_service_area or any other sibling. The description is a pure imperative with no context, exclusions, or alternative routing, leaving the agent to infer the selection logic.

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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