calc.engineer

solar load audit

solar_load_audit

Calculates total daily energy consumption from an appliance list — the critical first step before sizing solar panels or batteries. Enter each appliance with its wattage, hours of daily use, and quantity. Outputs total daily kWh (with configurable safety margin for surge and inrush current), peak simultaneous wattage, and recommended inverter VA rating per NEC 125% continuous load rule. Feeds directly into solar_sizing (daily_kwh) and battery_autonomy (daily_kwh). Essential for residential, RV, cabin, and off-grid system design.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`appliances`	Yes	List of appliances with wattage, hours per day, and quantity
`safety_margin_pct`	No	Safety margin percentage to account for surge/inrush current, default 20%

Output Schema

TableJSON Schema

Name	Required	Description
`peak_watts`	Yes	Peak simultaneous wattage if all appliances run at once (W)
`total_daily_wh`	Yes	Total daily energy consumption in watt-hours (Wh)
`appliance_count`	Yes	Total number of appliance entries
`total_daily_kwh`	Yes	Total daily energy consumption in kilowatt-hours (kWh)
`with_margin_kwh`	Yes	Daily kWh including safety margin
`largest_load_watts`	Yes	Wattage of the single largest appliance (W)
`recommended_inverter_va`	Yes	Recommended inverter size in VA (peak watts * 1.25 per NEC)

TDQS

A4.3/5.0

Behavior4/5

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

No annotations provided, so the description carries the full burden. It discloses that outputs include total daily kWh with configurable safety margin, peak simultaneous wattage, and recommended inverter VA rating per NEC rule. It does not mention any destructive behavior or auth needs, which is expected for a calculator.

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 concise at 4 sentences, front-loaded with purpose, and each sentence adds value. No redundant or irrelevant information.

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?

With an output schema present, the description doesn't need to detail return values. It covers the tool's purpose, key outputs, and integration with other tools, making it complete given the complexity.

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

Parameters3/5

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

Schema coverage is 100%, so baseline is 3. The description adds context about the safety margin accounting for surge/inrush current, but does not significantly extend parameter meaning 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?

The description clearly states the tool calculates total daily energy consumption from an appliance list, which is the critical first step for sizing solar panels or batteries. It also explicitly mentions it feeds into solar_sizing and battery_autonomy, distinguishing it from sibling tools.

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 description provides clear context for when to use this tool (first step before sizing) and mentions its outputs are used by other tools (solar_sizing, battery_autonomy). It does not explicitly state when not to use or list alternatives, but the context is sufficient.

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

Despite 89 tools, each has a clearly distinct purpose with detailed descriptions that often reference related tools. Overlap exists (e.g., multiple LoRa/RF tools), but the descriptions are sufficient to distinguish them. Some confusion possible among similar-sounding tools like attenuator_pi and attenuator_tee, but the descriptions explicitly compare them.

Naming Consistency4/5

Consistent underscore-separated lowercase naming. Most tools follow a verb_noun pattern (e.g., capacitor_charge, wire_gauge) or noun_noun (power_cost). Minor inconsistencies such as 'bmi_calculator' vs 'solar_sizing' but overall predictable.

Tool Count2/5

89 tools is far too many for a single MCP server. This scope is more appropriate for multiple specialized servers. The sheer number will slow agent selection and increase cognitive load, reducing coherence.

Completeness3/5

Covers many domains (RF, solar, PCB, networking, math, etc.) but lacks depth in some areas (e.g., no three-phase power, no airflow calculations). Some domains have comprehensive coverage (LoRa/Meshtastic), but others feel incomplete for the tool count.

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