vectorbt
무료High-performance vectorized backtesting with parameter optimization, portfolio simulation, and rich performance metrics
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High-performance vectorized backtesting with parameter optimization, portfolio simulation, and rich performance metrics
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This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions
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Quantum computing framework for building, simulating, optimizing, and executing quantum circuits. Use this skill when working with quantum algorithms, quantum circuit design, quantum simulation (noiseless or noisy), running on quantum hardware (Google, IonQ, AQT, Pasqal), circuit optimization and compilation, noise modeling and characterization, or quantum experiments and benchmarking (VQE, QAOA, QPE, randomized benchmarking).
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mdtraj molecular dynamics trajectory analysis (Python). Reads DCD/XTC/TRR/NetCDF/H5/PDB topologies and trajectories; computes RMSD vs time, radius of gyration, per-residue RMSF, residue-residue contact frequency maps, phi/psi torsions for Ramachandran plots (general + Gly/Pro), and 8-state DSSP secondary structure. Modules: trajectory I/O, geometry (distances/angles/dihedrals), structural analysis (RMSD/Rg/RMSF/SASA), contacts, hydrogen bonds, secondary structure (DSSP), NMR observables. For broader atom-selection grammar use mdanalysis-trajectory; for running MD simulations use OpenMM/GROMACS.
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Python toolkit for neurophysiological signal processing: ECG (HR, HRV, R-peaks), EEG (complexity, PSD), EMG (activation onset), EDA/GSR (SCR decomposition), PPG, and RSP. Includes synthetic signal simulation. Alternatives: BioSPPy (less maintained), MNE (EEG/MEG specialist), heartpy (ECG only), scipy.signal (raw DSP).
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Art direction for strategy, RTS, turn-based strategy, tower defense, MOBA, city builder, colony sim, and simulation games in Blender.
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Garment blockout, cloth simulation, pin groups, and bake to shape keys or caches for characters and props in Blender via MCP.
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Create 4D construction simulations by linking BIM models with project schedules.
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Link BIM elements to schedule activities for 4D simulation. Visualize construction sequence over time.
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Calculate risk-adjusted cost estimates using CWICR data. Apply contingencies, Monte Carlo simulation, and probability distributions to cost estimates.
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Optimize construction site logistics including material delivery scheduling, crane positioning, storage area allocation, and traffic flow using operations research and simulation.
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Use when your human partner has explicitly opted into exploratory or feasibility mode - a compute-heavy simulation, an unproven pipeline, an unbenchmarked solver, an untested cluster job - or when whether the work can run at all is still unknown, when a plan's largest configuration has never been executed, when a memory or wall-clock ceiling is estimated rather than measured, or when someone proposes pre-registering over runs that have never happened
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Route Flower repository tasks for app authoring, strategies and mods, local simulation and deployment, Flower Datasets and examples, and repository maintenance.
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Use DeepMind dm_control for MuJoCo simulation, Control Suite environments, PyMJCF models, Composer tasks, rendering, and high-level locomotion/manipulation workflows.
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Use Brian2 for clock-driven spiking-neural-network modeling, simulation, synaptic connectivity, input generation, recording, physical-unit equations, spatial neurons, runtime code generation, and C++ standalone workflows.
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Use AlpaSim repository guidance for autonomous-driving simulation setup, Hydra wizard runs, runtime services, ego drivers and plugins, ASL evaluation, controller/physics/traffic components, gRPC contracts, and operational troubleshooting.
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Routes ACT++, ACT, Diffusion Policy, VINN, and MuJoCo simulation workflows for bimanual ALOHA episode data and imitation-learning tasks.
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Search and inspect the installed Blueish Blender Asset Library without mutating it. Use when a user asks for a local Blender asset, node preset, Blueish asset, Asset Browser entry, or named source, or when the Router has selected a node-centric/reusable Geometry Nodes, material, simulation, rigging, compositor, or NPR route with eligible local catalogs; return compatible, attributable candidates for the Router-approved workflow.
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Build efficient Blender repetition, Array-driven stairs/modules/openings, instancing, scattering, Bezier/NURBS curve-profile geometry, Geometry Nodes fields, repeat zones, simulation zones, particle-like systems, and collective motion. Use for stairs, railings, trim, pipes, cables, repeated windows/panels, vegetation, debris, crowds, rain, snow, modular structures, or any request involving dependent elements or reusable parameters.
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Build, inspect, audit, and refactor Blender Geometry Nodes systems for procedural models, instancing, modular effects, curves, scattering, flocks, data visualization, fields, simulation zones, and node-graph cleanup. Use whenever a Blender task specifically calls for Geometry Nodes, reusable procedural node graphs, node connections/layout, or a scalable procedural asset.
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Design, configure, test, bake, and validate Blender physical effects including Cloth, Soft Body, Rigid Body, collisions, constraints, Fluid, smoke, fire, Dynamic Paint, Ocean, Wave, particles, Boids, force fields, fracture, debris, and secondary effects. Use when gravity, inertia, collision, flexibility, pressure, flow, flocking, emission, or breaking causes the requested result.
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Cloudflare Workers local development with Wrangler, Miniflare, hot reload, debugging. Use for project setup, wrangler.jsonc configuration, or encountering local dev, HMR, binding simulation errors.
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Think and work like an expert Mathematical Statistician. Use when a task calls for Mathematical Statistician judgment. Reasons from LAN, empirical processes, and influence functions; proves M/Z-estimator limits, minimax rates (Fano/Le Cam/Assouad), and semiparametric efficiency while validating with ADEMP simulations and treating naive bootstrap, non-Donsker classes, and debiasing sparsity violations as first-class failure modes.
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Think and work like an expert Manufacturing Engineer. Use when a task calls for Manufacturing Engineer judgment. Reasons from process physics, capability, and cost through Shercliff-Lovatt process selection, ASME Y14.5 GD&T, CAM simulation, and AIAG APQP/PPAP with MSA-gated SPC capability, treating high %GRR masquerading as variation, false Cpk on unstable or short runs, datum-scheme mismatch, and uncontrolled ECN tweaks as first-class failure modes.
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