calc.engineer

solar sizing

solar_sizing

Sizes an off-grid solar power system by calculating the number of panels and battery bank capacity required for a given daily energy consumption. Accounts for system losses (inverter, wiring, charge controller), battery depth-of-discharge, and autonomy days for cloudy weather. Outputs panel count, total panel wattage, battery capacity in kWh and Ah, and minimum charge controller amperage (with 25% safety margin per NEC 690.8). Supports 12V, 24V, and 48V system architectures. Use for cabin, RV, telecom tower, and remote IoT deployments.

Input Schema

TableJSON Schema

Name	Required	Description
`dod`	No	Battery depth of discharge (0-1), default 0.8 for LiFePO4
`daily_kwh`	Yes	Daily energy consumption in kilowatt-hours (kWh)
`panel_watts`	No	Rated wattage per solar panel (W)
`peak_sun_hours`	No	Average peak sun hours per day for your location (hours)
`system_voltage`	No	Battery bank system voltage: 12, 24, or 48 V
`system_efficiency`	No	Overall system efficiency (0-1), accounts for inverter, wiring, and controller losses
`battery_autonomy_days`	No	Number of days the battery bank should sustain load without solar input

Output Schema

TableJSON Schema

Name	Required	Description
`battery_ah`	Yes	Required battery bank capacity in amp-hours at system voltage
`battery_kwh`	Yes	Required battery bank capacity in kWh (before DoD)
`panels_needed`	Yes	Number of solar panels required (rounded up)
`daily_solar_kwh`	Yes	Daily solar energy needed after accounting for system losses (kWh)
`total_panel_watts`	Yes	Total installed panel wattage (W)
`charge_controller_amps`	Yes	Minimum charge controller current rating in amps (with 25% margin)

TDQS

A4.2/5.0

Behavior4/5

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

Discloses key behavioral traits: accounts for system losses (inverter, wiring, charge controller), battery depth-of-discharge, autonomy days, and applies a 25% safety margin per NEC 690.8 for charge controller sizing. With no annotations provided, this description carries the full burden and does so well, though it could explicitly state it is read-only (no side effects).

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?

Four well-structured sentences, front-loaded with purpose and outputs. Each sentence adds distinct value without redundancy. Highly concise and easy to parse.

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?

With 7 parameters and an output schema present, the description covers inputs, accounting factors, outputs, and target use cases. Lacks explicit mention of error handling or edge cases (e.g., unrealistic inputs) but is sufficient for intended use.

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 covers all 7 parameters with descriptions (100% coverage), baseline 3. The tool description adds contextual meaning beyond individual parameter descriptions, such as explaining that system losses include inverter, wiring, and charge controller, and that the charge controller amperage includes a 25% safety margin per NEC 690.8.

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?

Explicitly states it 'sizes an off-grid solar power system' by calculating panels and battery capacity. Lists specific outputs (panel count, wattage, battery kWh/Ah, charge controller amps). Distinguishes from siblings by specifying off-grid use cases like cabin, RV, telecom tower, and IoT.

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

Usage Guidelines3/5

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

Provides use cases ('cabin, RV, telecom tower, and remote IoT deployments') but does not explicitly contrast with sibling tools like solar_load_audit or solar_roi. No when-not-to-use guidance, leaving ambiguity for an agent selecting among related calculators.

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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