482 skills · sorted by relevance
Process-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any system where entities interact with shared resources over time.
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Quantum physics simulation library for open quantum systems. Use when studying master equations, Lindblad dynamics, decoherence, quantum optics, or cavity QED. Best for physics research, open system dynamics, and educational simulations. NOT for circuit-based quantum computing—use qiskit, cirq, or pennylane for quantum algorithms and hardware execution.
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Research computing toolkit for optoelectronic information science and engineering, MATLAB/Octave, Python scientific analysis, signal processing, image processing, statistics, simulation, optimization, publication figures, sensor/time-series data, citation lookup, and common scientific libraries. Use when the user asks for MATLAB code, scientific Python, data analysis, plots, simulations, formulas, statistics, machine learning, optical/physical/materials computation, or reproducible research workflows.
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Redistricting analysis in R using the redistverse ecosystem. Use whenever the user is working with redist, redistmetrics, ggredist, geomander, adj, alarmdata, PL94171, censable, easycensus, tinytiger, baf, rict, or redistio. Covers the complete pipeline: Census and spatial data loading, adjacency graph construction, SMC/MCMC simulation, constraints (population balance, county splits, VRA compliance), convergence diagnostics, plan metrics (compactness, partisan fairness, splits), visualization, summary tables, and interactive plan drawing. Invoke whenever the user mentions redistricting, gerrymandering, district plans, simulation ensembles, or any redistverse package by name.
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Process-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any system where entities interact with shared resources over time.
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Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.
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Connect the Newton physics engine to an Omniverse simulation or ovstage with ovnewton. Use when importing a populated ovstage into Newton, stepping its physics, synchronizing stage edits, or publishing simulation state for Omniverse rendering.
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Use this skill when calculating control system performance metrics such as rise time, overshoot percentage, steady-state error, or settling time for evaluating simulation results.
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Generate a browser-based p5.js curtain simulation that weaves user-supplied PNG, JPEG, or WebP artwork and optional text into individually moving strands. Use when users ask for an interactive curtain or thread simulation, artwork woven into cloth or ropes, image-bearing fabric motion, 可交互线帘/幕布, 图片织入布料, printed curtain effects, or a customizable browser-based fabric reveal.
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Build Simulink models that co-simulate with Eclipse SUMO traffic simulator. Use when creating SUMO-Simulink co-simulation, traffic simulation, TraCI connection, vehicle-in-the-loop testing, or ADAS scenario validation with SUMO. Covers Server/Client setup, Reader/Writer/Actor block configuration, random traffic generation, ego vehicle control, and SUMO file creation. Also use when the user mentions SumoInterfaceLibrary, .sumocfg files, or wants to connect Simulink to an external traffic simulator.
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Use when building or debugging Geometry Nodes, headless or live: procedural modeling, scattering objects on a surface, arrays along a curve, repeat or for-each loops, simulation zones, 5.2 physics (cloth, colliders, forces, effectors), closures, bundles, matrices, node-group assets with gizmos. Also when a GN script links nothing, shows red links, ignores modifier inputs, loses instances in a bounding box, or a simulation resets or jumps.
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This skill should be used when the user asks to "plan a red team engagement", "scope a penetration test", "design a security assessment methodology", "create rules of engagement", or "plan an adversary simulation".
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Structure a direct experience into a full learning cycle with concrete experience, reflection, and conceptual transfer. Use when planning field trips, simulations, or practical tasks.
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Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.
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Check reported lighting quantities and results in supplied simulation PDFs without adding repeated calculation surfaces. Use for scoped luminaire inventories and illuminance results; not simulation or compliance.
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Analyze MD trajectories from GROMACS, AMBER, NAMD, CHARMM, LAMMPS. Reads topology/trajectory into Universe objects; supports RMSD, RMSF, radius of gyration, contact maps, H-bonds, PCA, and custom distance/angle calculations. Use for post-simulation structural analysis; use OpenMM/GROMACS for running simulations.
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Process-based discrete-event simulation. Model queues, shared resources, timed events: manufacturing, service ops, network traffic, logistics. Processes are Python generators yielding events. Resources: capacity-limited (Resource/Priority/Preemptive), bulk (Container), objects (Store, FilterStore). For continuous use SciPy ODEs; for agent-based use Mesa.
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Testing strategies, patterns, and tools for robotics software. Use this skill when writing unit tests, integration tests, simulation tests, or hardware-in-the-loop tests for robot systems. Trigger whenever the user mentions testing ROS nodes, pytest with ROS, launch_testing, simulation testing, CI/CD for robotics, test fixtures for sensors, mock hardware, deterministic replay, regression testing for robot behaviors, or validating perception/planning/control pipelines. Also covers property-based testing for kinematics, fuzz testing for message handlers, and golden-file testing for trajectories.
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Create 4D construction simulations by linking BIM elements to project schedules. Generate time-based visualizations, sequence analysis, and construction phasing with Gantt integration.
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Building energy simulation and analysis for construction. Calculate heating/cooling loads, evaluate envelope performance, optimize HVAC sizing, and ensure energy code compliance.
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Turn one line ("a turbofan jet engine", "a mechanical watch", "an LVAD heart pump") into a photoreal, physics based, interactive 3D simulation of that machine in a single HTML file, plus a 20 to 30 second film to post it. Real proportions in metres, real materials (PBR metals, paints, polymers, glass), studio lighting with soft shadows, moving parts driven by a small solver that computes real numbers (thrust, torque, rpm, flow, pressure, efficiency), and modes to explode it, cut it open with clean section caps, x-ray it, slow it down, label it and break it. Use this whenever someone asks to build, simulate, visualise, explain or "show how X works" for any machine, engine, mechanism, device, instrument or piece of hardware, wants an interactive 3D model or a cutaway, or wants a video of a machine for a post, even if they never say "simulation" or "three.js".
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Fix Monte Carlo project completion simulations that give identical dates for all sub-groups (milestones, priorities, epics). Use when: (1) All sub-group predictions converge to the same date despite different remaining counts, (2) Proportional throughput scaling produces flat/identical results, (3) Applying overall scope rate to individual sub-groups causes simulations to hit max_weeks cap and never converge, (4) Building project forecasting tools that predict completion for sub-groups of a larger backlog. Covers hypergeometric draw model for milestones and cumulative priority model for sequential priorities.
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Orchestrate production-grade Blender work by probing the installed Blender version, retrieving relevant official Blender documentation, assigning visual design intent, classifying shape grammar and geometry/deformation/procedural/physics/shading needs, comparing direct Blender components with node systems, creating staged artifacts, and routing to specialist skills. Use for every non-trivial Blender creation, reconstruction, simulation, animation, environment, or scene-modification request, especially when the user does not know whether to use topology, Boolean, Array, curves, snapping, Displace, simulation, Geometry Nodes, or shading.
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Audit Blender scenes and assets for topology, transforms, normals, surface continuity, classified connections, intersections, modifier/node intent, procedural performance, simulation stability, protected-scene changes, and fixed-view visual evidence. Use after every major modeling or simulation stage and before render, bake, export, or claims of completion.
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