materials-simulation-skills

In the author's own words, from each skill's SKILL.md.

• convergence-study

  Perform spatial and temporal convergence analysis for solution verification — compute observed convergence orders from grid or timestep refinement studies, apply Richardson extrapolation to estimate discretization error, and calculate the Grid Convergence Index (GCI) per ASME V&V 20 standards. Use when verifying that a numerical solution converges at the expected rate, estimating the error on the…

  skills/core-numerical/convergence-study/SKILL.md on GitHub (opens in a new tab)

• differentiation-schemes

  Select and apply numerical differentiation schemes for PDE and ODE discretization — generate finite-difference stencils at arbitrary order and accuracy, choose between central, upwind, compact (Pade), and spectral methods, handle boundary stencils, and estimate truncation error scaling. Use when discretizing spatial derivatives, picking a scheme for advection- or diffusion-dominated problems, bui…

  skills/core-numerical/differentiation-schemes/SKILL.md on GitHub (opens in a new tab)

• linear-solvers

  Select and configure linear solvers for Ax=b systems arising in numerical simulations — choose between direct (LU, Cholesky) and iterative (CG, GMRES, BiCGSTAB, MINRES) methods, analyze sparsity patterns and matrix conditioning, recommend preconditioners (AMG, ILU, IC), apply row/column scaling, and diagnose convergence stagnation from residual histories. Use when setting up a linear solve for FE…

  skills/core-numerical/linear-solvers/SKILL.md on GitHub (opens in a new tab)

• mesh-generation

  Plan and evaluate mesh generation for numerical simulations — estimate grid resolution from physics scales (interface width, boundary layers, wavelengths), check aspect ratios and skewness against quality thresholds, choose between structured, unstructured, and adaptive mesh refinement strategies, and compute grid sizing for 1D/2D/3D domains. Use when setting up a new mesh, diagnosing poor solver…

  skills/core-numerical/mesh-generation/SKILL.md on GitHub (opens in a new tab)

• nonlinear-solvers

  Select and configure nonlinear solvers for root-finding f(x)=0, optimization min F(x), and least-squares problems — choose among Newton, Newton-Krylov, quasi-Newton (BFGS, L-BFGS), Broyden, Anderson acceleration, and Levenberg-Marquardt methods, configure line search or trust-region globalization, diagnose convergence rate (quadratic, linear, stagnated), and assess Jacobian quality and conditioni…

  skills/core-numerical/nonlinear-solvers/SKILL.md on GitHub (opens in a new tab)

• numerical-integration

  Select and configure time integration methods for ODE and PDE simulations — choose among explicit Runge-Kutta, BDF, Rosenbrock, and Adams families, set relative and absolute error tolerances, implement adaptive step-size control with P/PI step-size controllers, plan IMEX operator splitting for mixed stiff and non-stiff terms, and estimate splitting errors. Use when picking an integrator for a new…

  skills/core-numerical/numerical-integration/SKILL.md on GitHub (opens in a new tab)

• numerical-stability

  Analyze numerical stability for time-dependent PDE simulations — check CFL and Fourier criteria, perform von Neumann stability analysis, detect stiffness, evaluate matrix conditioning, and recommend explicit vs implicit time-stepping schemes. Use when selecting time steps, diagnosing numerical blow-up or solver divergence, checking convergence criteria, or evaluating scheme stability for advectio…

  skills/core-numerical/numerical-stability/SKILL.md on GitHub (opens in a new tab)

• time-stepping

  Plan and control time-step policies for transient simulations — couple CFL and physics-based stability limits with adaptive stepping, ramp initial transients through sharp gradients or phase changes, schedule output intervals and checkpoint cadence, and plan restart strategies for long-running jobs. Use when choosing dt for a new simulation, diagnosing adaptive time-step oscillations, deciding ch…

  skills/core-numerical/time-stepping/SKILL.md on GitHub (opens in a new tab)

• fair-simulation-packager

  Create FAIR-minded reproducibility bundles for materials simulations by collecting input/output file inventories, hashes, units, engine versions, structure identifiers, provenance, and NOMAD/OPTIMADE/Materials Project friendly metadata. Use before publishing, sharing, archiving, or handing simulation results to another agent.

  skills/data-management/fair-simulation-packager/SKILL.md on GitHub (opens in a new tab)

• hpc-runtime-doctor

  Diagnose HPC runtime and scheduler problems for materials simulations, including MPI/OpenMP/GPU layout, modules, CUDA/Kokkos hints, scratch paths, walltime, job arrays, restart strategy, scheduler portability, and resource mismatch. Use when an ALREADY-SUBMITTED job failed, ran slowly, got killed, or behaved differently on a cluster than on a workstation. To author or vet a NEW submission script…

  skills/hpc-deployment/hpc-runtime-doctor/SKILL.md on GitHub (opens in a new tab)

• slurm-job-script-generator

  Generate correct, copy-pasteable SLURM sbatch job scripts and sanity-check HPC resource requests — configure nodes, MPI tasks, OpenMP threads, memory (per-node or per-cpu), GPUs, walltime, partitions, modules, and environment variables, with automatic detection of conflicting directives and oversubscription. Use when preparing a SLURM submission script, deciding between pure MPI and hybrid MPI+Op…

  skills/hpc-deployment/slurm-job-script-generator/SKILL.md on GitHub (opens in a new tab)

• skill-evaluator

  Rigorously evaluate an Agent Skill end-to-end across ANY coding-agent CLI — verify its scripts emit the documented numbers (deterministic checks), test whether its description triggers on the right prompts, and measure whether an agent following the SKILL.md beats a no-skill baseline (with/without pass-rate delta, mean ± stddev, benchmarked). Use whenever you need to test, benchmark, validate, gr…

  skills/meta/skill-evaluator/SKILL.md on GitHub (opens in a new tab)

• ontology-explorer

  Parse, navigate, and query materials science ontology structures — browse class hierarchies, inspect individual classes and their properties, look up object and data property definitions with domain/range, search for ontology terms by keyword, and parse or summarize raw OWL/XML files. Currently supports CMSO and ASMO; the broader OCDO ecosystem (CDCO, PODO, PLDO, LDO) is planned. Use when explori…

  skills/ontology/ontology-explorer/SKILL.md on GitHub (opens in a new tab)

• ontology-mapper

  Map materials science terms, crystal structures, and sample descriptions to standardized ontology classes and properties — resolve natural-language concepts to ontology entries with confidence scores, translate Bravais lattice types, space groups, and lattice constants into ontology-compliant annotations, and produce full sample metadata from structured descriptions. Supports any ontology in onto…

  skills/ontology/ontology-mapper/SKILL.md on GitHub (opens in a new tab)

• ontology-validator

  Validate material sample annotations against ontology constraints — check that class names and property names exist in the ontology, verify domain and range consistency for object property relationships, assess annotation completeness (required, recommended, and optional properties), and flag unknown or misspelled terms. Use when verifying that CMSO or other ontology annotations are correct befor…

  skills/ontology/ontology-validator/SKILL.md on GitHub (opens in a new tab)

• simulation-failure-triage

  First-response triage for cross-code (LAMMPS/VASP/QE/MOOSE) simulation failures: classifies the failure signature (nonconvergence, NaN/Inf, exploding energy, unstable timestep, pressure blow-up, missing potentials/pseudopotentials, memory exhaustion, process crash/segfault, corrupted output, incomplete runs) and proposes a SAFE one-change-at-a-time RETRY LADDER with explicit STOP CONDITIONS, prio…

  skills/robustness/simulation-failure-triage/SKILL.md on GitHub (opens in a new tab)

• md-analysis-planner

  Plan molecular dynamics post-processing for materials simulations, including RDF, MSD and diffusion, VACF/VDOS, coordination numbers, bond-angle distributions, stress-strain curves, equilibration detection, PBC unwrapping, and trajectory format choices. Use before writing MD analysis scripts or trusting trajectory-derived results.

  skills/simulation-workflow/md-analysis-planner/SKILL.md on GitHub (opens in a new tab)

• parameter-optimization

  Explore and optimize simulation parameters via design of experiments (DOE), sensitivity analysis, and optimizer selection — generate Latin Hypercube, quasi-random, or factorial sample plans, rank parameter influence with sensitivity scores, recommend Bayesian optimization, CMA-ES, or gradient- based methods based on dimension and budget, and fit surrogate models for expensive evaluations. Use whe…

  skills/simulation-workflow/parameter-optimization/SKILL.md on GitHub (opens in a new tab)

• performance-profiling

  Identify computational bottlenecks, analyze parallel scaling, estimate memory requirements, and generate optimization recommendations for materials simulations — parse timing logs to find dominant phases (solver, assembly, I/O), evaluate strong and weak scaling efficiency, profile memory from mesh and field parameters, and detect bottlenecks with actionable fix suggestions. Use when a simulation…

  skills/simulation-workflow/performance-profiling/SKILL.md on GitHub (opens in a new tab)

• post-processing

  Extract, analyze, and summarize simulation output data — pull spatial fields at specific timesteps, compute time-series trends and detect steady state, extract line profiles through the domain, generate statistical summaries and distributions, calculate derived quantities (gradients, fluxes, volume fractions, interface area), compare results against analytical solutions or experimental data, and…

  skills/simulation-workflow/post-processing/SKILL.md on GitHub (opens in a new tab)

• simulation-orchestrator

  Orchestrate multi-simulation campaigns — generate parameter sweep configurations (grid, linspace, or Latin Hypercube sampling), initialize and track batch job campaigns, monitor job completion status, and aggregate results with summary statistics across all runs. Use when running a parameter study across dt, kappa, or other simulation inputs, managing dozens or hundreds of simulation configuratio…

  skills/simulation-workflow/simulation-orchestrator/SKILL.md on GitHub (opens in a new tab)

• simulation-validator

  Validate simulations across three stages — run pre-flight checks on configuration files (parameter ranges, required fields, disk space), monitor runtime logs for residual growth, NaN/Inf, and adaptive dt collapse, and perform post-flight validation of results (physical bounds, mass/energy conservation, convergence). Diagnose failed simulations with probable-cause analysis and recommended fixes. U…

  skills/simulation-workflow/simulation-validator/SKILL.md on GitHub (opens in a new tab)

• workflow-engine-mapper

  Map computational materials tasks onto workflow engines such as atomate2, jobflow, AiiDA, pyiron, or a simple one-off script. Use when deciding how to structure a reproducible campaign, DAG, restart strategy, provenance record, storage layout, or migration path from ad hoc scripts to managed workflows.

  skills/simulation-workflow/workflow-engine-mapper/SKILL.md on GitHub (opens in a new tab)

• benchmark-and-mms-planner

  Plan verification and validation campaigns for simulation codes using manufactured solutions, canonical benchmark problems, grid/time refinement, uncertainty propagation, and pass/fail acceptance criteria. Use when an agent needs to prove a solver, model, or result is trustworthy rather than only plausible.

  skills/verification-validation/benchmark-and-mms-planner/SKILL.md on GitHub (opens in a new tab)

No skill matches that filter.

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