Plugin Development

AutoMOOSE’s plugin registry allows you to add new physics modules without modifying the core agent pipeline. Each plugin implements a minimal two-function contract, and the orchestration layer, MCP server, and UI require no changes when a new plugin is added.

Available plugins

Plugin	Status	Notes
Grain Growth (Allen–Cahn)	validated	Non-conserved order parameters; two formulations (GBEvolution, LinearizedInterface), 2D/3D, seven presets.
Spinodal Decomposition (Cahn–Hilliard)	validated	Conserved order parameter; includes a CALPHAD-based Fe–Cr free-energy mode validated against exact mass conservation and free-energy dissipation.
Ferroelectric Switching (Landau–Ginzburg–Devonshire)	stub	Registered for future implementation.
Solidification (Allen–Cahn dendritic)	stub	Registered for future implementation.

Plugin Interface

from automoose.plugins import PhysicsPlugin, register_plugin

class MyPlugin(PhysicsPlugin):
    name = "MyPhysics"

    def generate_input(self, **params) -> str:
        """
        Generate a complete MOOSE .i input file string.

        Parameters
        ----------
        **params : dict
            Simulation parameters from the Architect agent.

        Returns
        -------
        str
            Valid MOOSE input file content.
        """
        ...

    def parse_results(self, csv_data: str) -> dict:
        """
        Parse MOOSE postprocessor CSV output.

        Parameters
        ----------
        csv_data : str
            Raw CSV string from MOOSE postprocessor output.

        Returns
        -------
        dict
            Structured results dictionary.
        """
        ...

register_plugin(MyPlugin)

Verification invariants

When you add a plugin, you can register physics-grounded falsification invariants for the Skeptic agent (\(f_6\)). These are exact or quantitative laws the result must obey — for example, mass conservation and free-energy dissipation for conserved (Cahn–Hilliard) dynamics, or monotonic coarsening and parabolic scaling for grain growth. The Skeptic uses them to issue a credibility verdict on each completed run.

Common Pitfalls

Based on lessons from the GrainGrowth plugin development:

• Duplicate block declarations — each MOOSE block (e.g. [Kernels]) must appear exactly once.

• Duplicate solver parameters — parameters like nl_abs_tol cannot appear in both [Executioner] and [Preconditioning].

• Unused parameters — MOOSE aborts on unrecognized parameters; check run.log with grep "ERROR\\|unused".