Topic · Data and Research
Materials Science and Simulation skills for Claude Code and Codex
Skills for computational materials science and numerical simulation: pymatgen structures, CALPHAD equilibria, molecular dynamics planning, battery simulation with PyBaMM, materials ontologies, and a full HeshamFS toolkit for solvers, mesh generation, time stepping, convergence studies, HPC job scripts and simulation failure triage. They give an agent the numerical habits that keep simulations stable.
Highest-scoring materials science skills in the October 22, 2026 snapshot: hpc-runtime-doctor from HeshamFS/materials-simulation-skills (85/100). Scores come from the Suede Skill Check.
- 31 listed skills
- 3 repositories
- 12 with full pages
2 from official publishers. 28 bundle scripts. 3 connect to an outside service. Listed in Science and Research (31).
All 31 materials science skills
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| Skill | Repository | What it does |
|---|---|---|
| convergence-study 84/100 · B | HeshamFS/materials-simulation-skills | Performs spatial and temporal convergence analysis for numerical solutions, computing observed convergence orders, Richardson extrapolation, and Grid Convergence Index per ASME V&V 20. |
| differentiation-schemes 82/100 · B | HeshamFS/materials-simulation-skills | Selects and applies numerical differentiation schemes for PDE and ODE discretization, including finite-difference stencils, central, upwind, compact and spectral methods. |
| hpc-runtime-doctor 85/100 · B | HeshamFS/materials-simulation-skills | Diagnoses HPC runtime and scheduler problems for already-submitted materials simulation jobs that failed, ran slowly, were killed, or behaved differently on a cluster. |
| linear-solvers 82/100 · B | HeshamFS/materials-simulation-skills | Selects and configures linear solvers for Ax=b systems, covering direct and iterative methods, preconditioners, sparsity and conditioning analysis, and diagnosing convergence stagnation. |
| mesh-generation 82/100 · B | HeshamFS/materials-simulation-skills | Plans and evaluates mesh generation for numerical simulations, covering grid resolution, mesh quality checks, and structured, unstructured, or adaptive refinement choices. |
| nonlinear-solvers 82/100 · B | HeshamFS/materials-simulation-skills | Selects and configures nonlinear solvers for root-finding, optimization, and least-squares problems, including Newton variants, quasi-Newton methods, globalization, and convergence rate diagnosis. |
| numerical-integration 82/100 · B | HeshamFS/materials-simulation-skills | Selects and configures time integration methods for ODE and PDE simulations, including error tolerances, adaptive step-size control, and IMEX operator splitting. |
| numerical-stability 84/100 · B | HeshamFS/materials-simulation-skills | Analyzes numerical stability for time-dependent PDE simulations, covering CFL and Fourier criteria, von Neumann analysis, stiffness detection, and explicit versus implicit time-stepping recommendations. |
| ontology-explorer 82/100 · B | HeshamFS/materials-simulation-skills | Parses, navigates, and queries materials science ontology structures, including class hierarchies, property definitions, term search, and OWL/XML summaries, currently for CMSO and ASMO. |
| ontology-mapper 82/100 · B | HeshamFS/materials-simulation-skills | Maps materials science terms, crystal structures, and sample descriptions to standardized ontology classes and properties, producing ontology-compliant annotations and sample metadata. |
| ontology-validator 82/100 · B | HeshamFS/materials-simulation-skills | Validates material sample annotations against ontology constraints, checking that terms exist, relationships are consistent, and required properties are present. |
| parameter-optimization 82/100 · B | HeshamFS/materials-simulation-skills | Explores and optimizes simulation parameters using design of experiments, sensitivity analysis, optimizer selection, and surrogate models, including parameter sweep planning. |
| benchmark-and-mms-planner 81/100 · B | HeshamFS/materials-simulation-skills | Plan verification and validation campaigns for simulation codes using manufactured solutions, canonical benchmark problems, grid/time refinement… |
| cudaq-guide 79/100 · C | NVIDIA/skills | Use for CUDA-Q setup, simulation targets, QPU access, and @cudaq.kernel authoring guidance. |
| cuopt-numerical-optimization-formulation 68/100 · D | NVIDIA/skills | LP, MILP, QP — concepts, problem-text parsing, and formulation patterns (parameters, constraints, decisions, objective). Concepts only; no API. |
| fair-simulation-packager 73/100 · C | HeshamFS/materials-simulation-skills | Create FAIR-minded reproducibility bundles for materials simulations by collecting input/output file inventories, hashes, units, engine versions… |
| fluidsim 89/100 · B | K-Dense-AI/claude-scientific-skills | Plans, configures, inspects, restarts, and analyzes bounded FluidSim computational-fluid-dynamics simulations with explicit numerical-validity and… |
| md-analysis-planner 73/100 · C | HeshamFS/materials-simulation-skills | Plan molecular dynamics post-processing for materials simulations, including RDF, MSD and diffusion, VACF/VDOS, coordination numbers, bond-angle… |
| molecular-dynamics 77/100 · C | K-Dense-AI/claude-scientific-skills | Runs and analyzes molecular dynamics simulations with OpenMM and MDAnalysis. Sets up protein/small molecule systems, defines force fields, runs… |
| performance-profiling 82/100 · B | HeshamFS/materials-simulation-skills | Identify computational bottlenecks, analyze parallel scaling, estimate memory requirements, and generate optimization recommendations for materials… |
| post-processing 82/100 · B | HeshamFS/materials-simulation-skills | Extract, analyze, and summarize simulation output data — pull spatial fields at specific timesteps, compute time-series trends and detect steady… |
| pybamm 87/100 · B | K-Dense-AI/claude-scientific-skills | Simulates lithium-ion battery charge, discharge and rest experiments with PyBaMM, records parameter-set provenance, checks mesh and solver… |
| pycalphad 87/100 · B | K-Dense-AI/claude-scientific-skills | Computes finite-temperature CALPHAD equilibria, phase fractions, and phase compositions from thermodynamic TDB databases using pycalphad. Use for… |
| pymatgen 89/100 · B | K-Dense-AI/claude-scientific-skills | Analyzes, validates, converts, and transforms materials structures and computed materials data with pymatgen. Use for local phase diagrams, symmetry… |
| simpy 89/100 · B | K-Dense-AI/claude-scientific-skills | Builds, inspects, tests, and analyzes bounded process-based discrete-event simulations with SimPy. Use for event scheduling, resource queues… |
| simulation-failure-triage 74/100 · C | HeshamFS/materials-simulation-skills | First-response triage for cross-code (LAMMPS/VASP/QE/MOOSE) simulation failures: classifies the failure signature (nonconvergence, NaN/Inf… |
| simulation-orchestrator 82/100 · B | HeshamFS/materials-simulation-skills | Orchestrate multi-simulation campaigns — generate parameter sweep configurations (grid, linspace, or Latin Hypercube sampling), initialize and track… |
| simulation-validator 82/100 · B | HeshamFS/materials-simulation-skills | Validate simulations across three stages — run pre-flight checks on configuration files (parameter ranges, required fields, disk space), monitor… |
| slurm-job-script-generator 82/100 · B | HeshamFS/materials-simulation-skills | Generate correct, copy-pasteable SLURM sbatch job scripts and sanity-check HPC resource requests — configure nodes, MPI tasks, OpenMP threads… |
| time-stepping 84/100 · B | HeshamFS/materials-simulation-skills | Plan and control time-step policies for transient simulations — couple CFL and physics-based stability limits with adaptive stepping, ramp initial… |
| workflow-engine-mapper 81/100 · B | HeshamFS/materials-simulation-skills | Map computational materials tasks onto workflow engines such as atomate2, jobflow, AiiDA, pyiron, or a simple one-off script. Use when deciding how… |
How to choose materials science skills
The HeshamFS materials-simulation collection is designed to work together: plan with the solver and stability skills, run with slurm-job-script-generator, and check with convergence-study and simulation-validator.
Many skills bundle Python scripts that compute stability limits or convergence orders. The scripts list on each page shows what runs and which packages it needs.
Use simulation-failure-triage and hpc-runtime-doctor when a job fails. They classify the failure from logs before you change parameters.
Related topics
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