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Topic: agents

2,643 skills in this topic.

parallel-debugging Debug complex issues using competing hypotheses with parallel investigation, evidence collection, and root cause arbitration. Use this skill when debugging bugs with multiple potential causes, performing root cause analysis, or organizing parallel investigation workflows.
wshobson/agents 32,911
multi-reviewer-patterns Coordinate parallel code reviews across multiple quality dimensions with finding deduplication, severity calibration, and consolidated reporting. Use this skill when organizing multi-reviewer code reviews, calibrating finding severity, or consolidating review results.
wshobson/agents 32,911
wcag-audit-patterns Conduct WCAG 2.2 accessibility audits with automated testing, manual verification, and remediation guidance. Use when auditing websites for accessibility, fixing WCAG violations, or implementing accessible design patterns.
wshobson/agents 32,911
screen-reader-testing Test web applications with screen readers including VoiceOver, NVDA, and JAWS. Use when validating screen reader compatibility, debugging accessibility issues, or ensuring assistive technology support.
wshobson/agents 32,911
react-modernization Upgrade React applications to latest versions, migrate from class components to hooks, and adopt concurrent features. Use when modernizing React codebases, migrating to React Hooks, or upgrading to latest React versions.
wshobson/agents 32,911
smalltalk-usage-finder Class and method usage analyzer for Pharo Smalltalk. Provides expertise in understanding class responsibilities through class comments (get_class_comment), discovering usage patterns via references (search_references_to_class), finding example methods (exampleXXX patterns), analyzing method usage in context (search_references with polymorphism handling), generating package overviews (list_classes with comment analysis), and resolving ambiguous names (search_classes_like, search_methods_like). Use when understanding what a class does, finding usage examples for classes or methods, discovering how to use an API, analyzing package structure and purpose, resolving unclear class or method names, or learning usage patterns from real-world code.
mumez/smalltalk-dev-plugin 9
smalltalk-implementation-finder Method implementation finder and analyzer for Pharo Smalltalk. Provides expertise in discovering implementors across class hierarchies (search_implementors), analyzing implementation patterns, learning coding idioms from existing implementations, assessing refactoring impact (counting implementors and references), finding duplicate code for consolidation, understanding abstract method implementations (subclassResponsibility), and tracing method overrides through inheritance chains. Use when analyzing method implementations across classes, learning implementation idioms, assessing refactoring risk before changes, finding duplicate implementations for consolidation, understanding how abstract methods are implemented in concrete classes, or tracing which classes override specific methods.
mumez/smalltalk-dev-plugin 9
smalltalk-developer Comprehensive Pharo Smalltalk development workflow guide with AI-driven Tonel editing. Provides expertise in Tonel file format syntax (class definitions with name, superclass, instVars, category, method categories, class comment placement), package structure (package.st placement, directory organization, BaselineOf dependencies), development workflow (Edit → Import → Test cycle with absolute paths, re-import timing, test execution), and Pharo best practices (CRC format documentation, method categorization conventions). Use when working with Pharo Smalltalk projects, creating or editing Tonel .st files, organizing packages and dependencies, resolving import order issues, writing class comments, implementing standard Pharo development patterns (Singleton, Settings, etc.), or troubleshooting Tonel syntax.
mumez/smalltalk-dev-plugin 9
smalltalk-debugger Systematic debugging guide for Pharo Smalltalk development. Provides expertise in error diagnosis (MessageNotUnderstood, KeyNotFound, SubscriptOutOfBounds, AssertionFailure), incremental code execution with eval tool, intermediate value inspection, error handling patterns (`on:do:` blocks), stack trace analysis, UI debugger window detection (read_screen for hung operations), and debug-fix-reimport workflow. Use when encountering Pharo test failures, Smalltalk exceptions, unexpected behavior, timeout or non-responsive operations, need to verify intermediate values, execute code incrementally for diagnosis, or troubleshoot Tonel import errors.
mumez/smalltalk-dev-plugin 9
smalltalk-commenter Generates CRC-style class comments for Smalltalk classes. Use after creating or modifying Tonel files to add or improve class documentation.
mumez/smalltalk-dev-plugin 9
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 produce automated analysis reports. Use when interpreting finished simulation results, checking mass or energy conservation, comparing two runs or meshes, extracting interface profiles from phase-field output, or preparing publication-quality analysis, even if the user only says "what do my results look like" or "did my simulation reach steady state."
HeshamFS/materials-simulation-skills 29
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 is running slower than expected, investigating MPI scaling efficiency, planning HPC resource allocation, deciding whether to tune the preconditioner or reduce I/O frequency, or estimating if a problem fits in available RAM, even if the user only says "my simulation is too slow" or "how many nodes do I need."
HeshamFS/materials-simulation-skills 29
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 when calibrating material properties against experimental data, planning a parameter sweep, performing uncertainty quantification, or choosing an optimization strategy for a simulation with a limited evaluation budget, even if the user only says "which parameters matter most" or "how do I calibrate my model."
HeshamFS/materials-simulation-skills 29
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 before publishing, checking whether all required properties are present for a class like Crystal Structure or Unit Cell, auditing relationship triples between instances, or catching annotation errors early in a FAIR data workflow, even if the user only says "is my annotation correct" or "what am I missing."
HeshamFS/materials-simulation-skills 29
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 ontology_registry.json (CMSO, ASMO, etc.). Use when annotating simulation inputs with FAIR metadata, translating "BCC iron" or "FCC copper" into formal ontology terms, preparing machine- readable sample descriptions, or bridging between lab vocabulary and ontology vocabulary, even if the user only says "what CMSO terms describe my material" or "annotate this sample for me."
HeshamFS/materials-simulation-skills 29
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. Supports the OCDO ecosystem (CMSO, ASMO, CDCO, PODO, PLDO, LDO). Use when exploring what classes or properties an ontology provides, finding the right CMSO term for a crystal structure or simulation concept, understanding parent-child class relationships, or onboarding to an unfamiliar materials ontology, even if the user only says "what ontology terms describe my FCC copper simulation" or "show me the CMSO class hierarchy."
HeshamFS/materials-simulation-skills 29
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+OpenMP layouts, standardizing #SBATCH directives across a team, debugging why a job won't launch or gets killed, or setting up GPU-accelerated simulation jobs, even if the user only says "I need to run this on the cluster" or "my job keeps getting killed."
HeshamFS/materials-simulation-skills 29
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 checkpoint frequency to minimize lost work, or setting up output schedules aligned with physical time scales, even if the user only says "my run is too slow" or "how often should I save."
HeshamFS/materials-simulation-skills 29
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 advection, diffusion, or reaction problems, even if the user doesn't explicitly mention "stability" or "CFL."
HeshamFS/materials-simulation-skills 29
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 I/PI/PID controllers, plan IMEX operator splitting for mixed stiff and non-stiff terms, and estimate splitting errors. Use when picking an integrator for a new simulation, diagnosing step rejections or tolerance failures, setting up operator splitting for phase-field or reaction-diffusion problems, or deciding between explicit and implicit time marching, even if the user only says "my solver keeps rejecting steps" or "which ODE method should I use."
HeshamFS/materials-simulation-skills 29
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 conditioning. Use when a Newton solver converges slowly or diverges, choosing between line search and trust region, debugging nonlinear iteration failures in FEM or phase-field codes, or selecting a solver for large-scale unconstrained optimization, even if the user only says "my Newton iterations aren't converging."
HeshamFS/materials-simulation-skills 29
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 convergence caused by mesh quality, deciding how many points to place across a phase-field interface or boundary layer, or preparing a mesh convergence study, even if the user only asks "what resolution do I need" or "why is my solver failing."
HeshamFS/materials-simulation-skills 29
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 FEM/FVM assembly, debugging slow or stalled Krylov iterations, choosing a preconditioner for SPD or nonsymmetric systems, or investigating ill-conditioning, even if the user only says "my solver is slow" or "GMRES won't converge."
HeshamFS/materials-simulation-skills 29
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, building custom stencils for nonstandard operators, or comparing dispersion and dissipation properties of candidate schemes, even if the user just says "how do I approximate this derivative" or "my solution is too diffusive."
HeshamFS/materials-simulation-skills 29