cx-chaos-nonlinear-dynamics

Analyze nonlinear dynamical systems, bifurcations, and deterministic chaos. Use for flows and maps, phase portraits, fixed points, limit cycles, Lyapunov exponents, Poincare sections, attractors, continuation, and distinguishing chaos from noise or numerical artifacts.

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Repository: eightmm/codex-science
Last source activity: July 10, 2026 at 13:08
Detected SKILL.md language: English
Stars: 2
Forks: 0

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quantitative-research

Execute auditable quantitative research across preregistered study design, statistical inference, numerical verification, dimensional analysis, uncertainty propagation, counterexample search, and formal proof. Use when a scientific or mathematical question needs actual computation and machine-readable evidence rather than only explanation.

2026-08-04

statistical-decision-analysis

Compare finite actions under uncertainty with explicit states, loss, utility or risk-neutral payoff, priors, experiment likelihoods, and a declared decision criterion. Use for Bayes risk, expected utility or payoff, pure-action minimax, minimax regret, dominance, posterior decision policies, EVPI/EVSI, experiment-cost decisions, and prior-threshold sensitivity; do not use for ordinary statistical testing, causal identification, strategic games, or MDP/POMDP/RL planning.

2026-08-04

cx-statistical-decision-analysis

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name	cx-chaos-nonlinear-dynamics
description	Analyze nonlinear dynamical systems, bifurcations, and deterministic chaos. Use for flows and maps, phase portraits, fixed points, limit cycles, Lyapunov exponents, Poincare sections, attractors, continuation, and distinguishing chaos from noise or numerical artifacts.