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
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Get business information for the OKC HVAC Calculator, powered by Covington Heat & Air (name, phone, email, website, service area).
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
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.
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.
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.
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.
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.
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.
Add one secure layer between your agents and this server.
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.
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.
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.
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.