Convert circuit netlists into Modified Nodal Analysis systems for solving.
npx skills add https://github.com/lgili/skillex --skill circuit-solver
Please help me install this Agent Skill. Skill: circuit-solver Source: https://github.com/lgili/skillex/tree/main/skills/circuit-solver Command: npx skills add https://github.com/lgili/skillex --skill circuit-solver
It provides a robust framework to convert circuit netlists into solvable Modified Nodal Analysis systems by augmenting node equations with branch currents and enforcing a ground reference, enabling accurate simulation of complex circuits.
Provide a circuit netlist and run the solver to obtain node voltages and branch currents.
High-intent search queries and answers about installing and using this skill.
To convert a circuit netlist into a Modified Nodal Analysis matrix, you stamp resistors, capacitors, inductors, and sources into a sparse Y matrix while augmenting node voltages with branch currents. This enforces the ground reference and builds the Y·x = J system for solving.
Solving nonlinear circuits with Newton-Raphson iterations requires assembling a sparse Y matrix and repeatedly restamping elements until convergence is reached. The solver handles nonlinear elements by formulating and iterating through NR steps to calculate node voltages and branch currents.
Re-stamping circuit matrices during switch state changes involves modifying the sparse Y matrix topology and applying incremental updates. This restamping process ensures the Y·x = J system accurately reflects the new circuit configuration before the next LU factorization.
Yes, MNA nodal analysis supports voltage and current controlled sources by applying specific stamping rules. These controlled elements are integrated directly into the sparse Y matrix alongside standard components to accurately solve the Y·x = J system.
Sparse matrix LU factorization fails to converge for nonlinear circuits when stamping rules are inconsistent or the ground reference is improperly enforced. Diagnosing convergence issues requires validating the matrix structure and ensuring proper Newton-Raphson iteration setup.
Yes, you can use sparse matrix assembly for circuit simulation without external dependencies. The solver independently assembles the sparse Y matrix and performs LU factorization or Newton-Raphson iterations natively using C++ implementations.
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