calc.engineer

wire gauge

wire_gauge

Determines the minimum AWG (American Wire Gauge) conductor size for a given current, voltage, one-way cable distance, and maximum allowable voltage drop percentage. Supports copper and aluminum conductors. Computes round-trip resistance, actual voltage drop in volts and percent, and wire cross-sectional area. Essential for DC solar runs, battery bank wiring, EV charging circuits, and low-voltage landscape lighting. NEC recommends 3% max drop for branch circuits and 5% total including feeder. Outputs the smallest AWG that satisfies the drop constraint.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`voltage`	Yes	System voltage (V)
`conductor`	No	Conductor material: copper or aluminum	copper
`distance_m`	Yes	One-way conductor distance in meters
`current_amps`	Yes	Load current in amperes (A)
`max_drop_pct`	No	Maximum allowable voltage drop as percentage (default 3%)

Output Schema

TableJSON Schema

Name	Required	Description
`insufficient`	Yes	True if even the largest AWG (4/0) cannot meet the voltage drop target
`actual_drop_v`	Yes	Actual voltage drop in volts
`wire_area_mm2`	Yes	Cross-sectional area of recommended gauge in mm^2
`actual_drop_pct`	Yes	Actual voltage drop percentage with recommended gauge
`recommended_awg`	Yes	Recommended AWG gauge number (smaller number = thicker wire)
`resistance_per_m`	Yes	Resistance per meter of the recommended gauge (ohm/m)
`recommended_awg_label`	Yes	Human-readable AWG label (e.g. '10' or '0000 (4/0)')

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It explains that the tool outputs the smallest AWG satisfying the drop constraint and lists computed values (resistance, drop in volts/percent, area). It does not disclose assumptions like conductor temperature, but for a calculator, this is acceptable; a 4 reflects good transparency with minor gaps.

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 5 sentences, front-loaded with the main action, covers outputs, use cases, and standards without unnecessary words. Excellent structure for quick comprehension.

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?

Given the tool's moderate complexity (5 parameters, output schema present), the description adequately covers functionality and use context. It lacks mention of error handling or limitations (e.g., no temperature derating), but it provides enough for an AI agent to invoke the tool correctly. A 4 reflects good completeness with minor omitted details.

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?

The input schema has 100% coverage, describing all 5 parameters with units and constraints. The description adds no additional semantic information beyond rephrasing the schema (e.g., 'given current' for current_amps). Baseline 3 is appropriate since the schema already handles parameter details.

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's purpose: determining minimum AWG conductor size based on current, voltage, distance, and voltage drop. It specifies supported materials (copper, aluminum) and distinguishes from sibling tools like wire_ampacity and voltage_drop by focusing on drop-constrained 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?

The description provides specific use cases (DC solar runs, battery bank wiring, EV charging, low-voltage lighting) and includes NEC recommendations for voltage drop limits. However, it does not explicitly state when not to use this tool or mention alternative tools for ampacity-based sizing, leaving some guidance implicit.

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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