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em_dc_resistance

Calculate exact DC resistance of a uniform conductor from length, area, and conductivity. Add voltage to also get current and Joule power in one step.

Instructions

Exact DC resistance of a uniform conductor (NO solver) — R = L/(σ·A), the closed-form anchor the Elmer em_conduction_submit gate reproduces to machine precision. With voltage_v the Ohm/Joule pair is included (I = V/R, P = V·I). σ from conductivity_s_m or a conductor name.

Returns {resistance_ohm, conductivity_s_m, length_m, area_m2, current_a?, joule_w?}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
area_mm2Yes
conductorNo
length_mmYes
voltage_vNo
conductivity_s_mNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does notable work: it declares the computation is closed-form with no solver, specifies the exact return payload including which fields are optional (current_a?, joule_w?), and states the conditional that produces them. It leaves unit handling and any validation/error behavior unstated, so it is not exhaustive, but the behavioral profile is well conveyed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Core purpose and formula are front-loaded, and the trailing Returns block efficiently covers the output. Three sentences plus one return clause, with essentially no filler; only marginal tightening is possible.

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?

For a pure math tool with no output schema and no annotations, the description supplies the formula, the computational nature, and the full return shape, which is what an agent needs to call it correctly. The missing unit semantics on the two required geometry inputs is the only substantive gap.

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 description coverage is 0%, so the description must supply all parameter meaning. It usefully explains conductivity_s_m vs the conductor-name alternative and the role of voltage_v, but says nothing about length_mm and area_mm2 (the two required params) or the fact that results are converted to meters in the return, leaving a real gap.

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?

States a specific verb+resource (exact DC resistance of a uniform conductor), gives the governing formula R = L/(σ·A), and explicitly frames itself against the sibling em_conduction_submit as the closed-form anchor with 'NO solver'. An agent can tell it apart from the FEM conduction path without opening any schema.

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 clearly positions this as the analytical/closed-form result that the em_conduction_submit gate reproduces, which implicitly tells the agent when to reach for this versus the solver, and it notes that passing voltage_v unlocks the Ohm/Joule output. It stops short of an explicit when-not or a direct routing sentence, but the context is strong.

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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