queuing-analyzer
Queuing theory analysis skill for analytical evaluation of waiting line systems.
tensor-network-simulator
Tensor network-based simulation skill for large circuit approximation
statevector-simulator
Full state vector simulation skill for exact quantum circuit evaluation
resource-estimator
Quantum resource estimation skill for algorithm feasibility analysis
qubo-formulator
QUBO (Quadratic Unconstrained Binary Optimization) formulation skill for optimization problems
simulation-experiment-designer
Simulation experimental design skill for efficient scenario analysis and optimization.
risk-distribution-fitter
Probability distribution fitting skill for calibrating uncertainty models from historical data or expert judgment
agent-based-simulator
Agent-based modeling skill for simulating complex adaptive systems with heterogeneous interacting agents
monte-carlo-engine
Monte Carlo simulation engine skill for probabilistic modeling, risk quantification, and uncertainty propagation
sensitivity-analyzer
Sensitivity analysis skill for identifying critical inputs and understanding model behavior under uncertainty
system-dynamics-modeler
System dynamics modeling skill for feedback loop analysis, stock-flow diagrams, and dynamic simulation
discrete-event-simulator
Discrete event simulation skill for modeling and analyzing complex systems with stochastic processes.
distribution-fitter
Statistical distribution fitting skill for input modeling in simulation and analysis.
thrivve-mc-when
Thrivve Partners Monte Carlo simulation to forecast completion date based on remaining work and historical throughput. Use when the user asks "when will I complete [N] stories/tasks" with historical daily throughput data. Requires at least 10 days of throughput history, a count of remaining items, and optional confidence level (default 85%).
thrivve-mc-how-many
Thrivve Partners Monte Carlo simulation to forecast story/task completion based on historical throughput. Use when the user asks "how many stories/tasks will be completed by [date]" with historical daily throughput data. Requires at least 10 days of throughput history and a future target date. Provides probabilistic forecasts at specified confidence levels (default 85%).
scenario-analyzer
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simulation-speed-adjustment
Adjust simulation temporal processing speed.
whole-brain-emulation-core-simulation
Simulate whole-brain emulation core processes.
computational-model-design
Design computational models for cognitive simulation and analysis.
gtnh-skill
This skill provides accurate data about GT New Horizons based on official data dumps. Use when answering questions about GTNH (GregTech New Horizons).
rosetta-helix-substrate
Consciousness simulation framework with Kuramoto oscillators, APL operators, and K-formation dynamics. Use for physics simulations, phase transitions, coherence analysis, and cloud training via GitHub Actions. Requires numpy and requests packages.
