Use when the user asks for systematic element substitution, combinatorial materials screening, high-throughput composition search, or multi-site replacement across different element groups.
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Diagnose and fix common VASP errors including ZBRENT, BRMIX, EDDDAV, VERY BAD NEWS, POTCAR mismatch, and memory errors.
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Diagnose and fix SCF and ionic convergence failures in VASP and ORCA. Covers ALGO, mixing parameters, ISMEAR, NELM, EDIFFG, NSW, and IBRION settings.
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Generate and manage ABINIT DFT calculations. Use when the user requests ABINIT, or needs DFPT phonons, GW calculations, or BSE optical spectra.
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Use when the user asks for adsorption energy, binding energy, or wants to compare how strongly a molecule binds to a surface.
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Use AmberTools antechamber for molecular force field parameterization. Generates GAFF/GAFF2 parameters and AM1-BCC or RESP charges for use in AMBER or LAMMPS classical MD simulations.
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Use when the user asks about Bader charge analysis, charge transfer, oxidation states from DFT, or electron density partitioning.
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Use when the user asks about CO2 reduction reaction (CO2RR), CO2 electroreduction intermediates, Faradaic efficiency, or selectivity toward CO, methanol, methane, formic acid, etc.
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Use when the user asks about COHP (Crystal Orbital Hamilton Population), chemical bonding analysis, LOBSTER output, orbital-resolved bonding, or bonding/antibonding character between atoms.
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Use when the user asks to test ENCUT convergence, k-point convergence, or any parameter sweep to determine converged computational settings.
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CP2K geometry optimization. Handles bulk, slab, and molecular systems with GPW method. Efficient for large systems (200+ atoms).
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CP2K single point energy calculation. Uses GTH pseudopotentials, Gaussian-plane-wave (GPW) method, and DZVP basis sets for periodic DFT.
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Run DeePMD-kit inference to predict energies, forces, and stresses using a trained DP model. Also covers model evaluation and testing.
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Train DeePMD-kit machine learning potentials. Covers DPA-3 (recommended), se_e2_a (legacy), and fine-tuning from pretrained models.
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Generate and manage DFTB+ calculations. Use when the user requests DFTB+, tight-binding DFT, SCC-DFTB, or needs fast approximate DFT for large systems or MD.
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Use when the user asks about density of states (DOS), projected DOS (PDOS), d-band center, spin-resolved DOS, or electronic structure analysis from completed DFT calculations.
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Convert between computational chemistry data formats using dpdata. Handles VASP, QE, CP2K, Gaussian, LAMMPS, and DeePMD formats. Essential for preparing ML potential training data.
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Use when the user asks to generate a reaction energy diagram, free energy profile, potential energy surface plot, or pathway comparison diagram for catalysis or reaction mechanism studies.
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Generate and manage Gaussian calculations. Use when the user requests Gaussian, G16, GJF files, or needs hybrid functionals (B3LYP), MP2, CCSD(T), or molecular quantum chemistry with Gaussian basis sets.
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Use when the user asks for Gibbs free energy, zero-point energy (ZPE), thermal corrections, or thermodynamic properties from DFT + frequency data.
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Generate and manage GPAW Python-based DFT calculations. Use when the user requests GPAW, Python DFT, real-space grid DFT, or LCAO-DFT with ASE integration.
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Use when the user asks about HER (hydrogen evolution reaction), hydrogen adsorption free energy, or volcano plot descriptor for HER catalysts.
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Automatically logs new discoveries to CLAUDE.md files. Triggers when fixing bugs, discovering pitfalls, finding performance issues, or learning new patterns in the codebase.
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Run LAMMPS molecular dynamics with DeePMD-kit machine learning potentials. Use when the user wants MD simulations driven by a trained DP model.
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