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jiweiqi

heatpump-mcp-server

calculate_heat_pump_sizing

Calculate required BTU for a single-zone heat pump using location, home size, and build year. Get model suggestions and oversizing warnings.

Instructions

Calculate required BTU capacity for a single-zone heat pump installation.

This tool performs a quick sizing calculation based on:

  • Home location (ZIP code) for climate zone and design temperature

  • Square footage and building age for heat loss estimation

  • Optional humidity considerations for enhanced dehumidification needs

Returns: Dictionary with: - required_btu: Recommended BTU capacity - btu_range_min/max: Acceptable range for equipment selection - design_temperature: Design heating temperature for location - climate_zone: ASHRAE climate zone - recommended_models: List of suitable heat pump models - calculation_notes: Detailed explanation of calculations - humidity_recommendations: Optional humidity control advice - oversizing_warnings: Warnings if system may be oversized

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zip_codeYes5-digit US ZIP code
square_feetYesHome square footage (100-10000)
build_yearYesYear home was built (1900-2025)
humidity_concernsNoDoes home have humidity issues?
humidity_levelNoHumidity level: low, normal, high, extremenormal
dehumidification_priorityNoPrioritize dehumidification capability

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations provided, so description carries full burden. It fully explains the calculation factors (climate zone via ZIP, square footage, build year, optional humidity) and lists all return fields, making the tool's behavior transparent.

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?

Description is well-structured with bullet points and a clear return list. Each sentence adds value, and the main purpose is front-loaded. No unnecessary words.

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?

Description adequately covers inputs and outputs for a sizing tool. It includes optional humidity considerations and detailed return fields. However, it could mention that the calculation is approximate (quick sizing) or any limitations.

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?

Schema has 100% description coverage, but the tool description adds meaningful context beyond basic schema descriptions (e.g., explains how ZIP code determines climate zone and design temperature). This adds value beyond the schema.

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?

Description clearly states it calculates required BTU capacity for a single-zone heat pump installation. It lists specific inputs (ZIP code, square footage, build year, humidity) and outputs, distinguishing it from sibling 'calculate_multi_zone_sizing'.

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?

Description clearly indicates when to use the tool (for single-zone sizing) but does not explicitly state when not to use or mention alternatives. The sibling list provides context, but the description lacks explicit exclusions.

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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