What problem does it solve? Systems engineers and risk analysts often need NASA-standard Probabilistic Risk Assessment methods mid-task but cannot recall the details of the 450-page NASA/SP-2011-3421 guide. This Skill loads reconstructed reference notes on demand so an AI agent can answer PRA questions accurately from the source material. ## Core Features & Use Cases - Scenario Logic Modeling: Covers the full risk triplet and logic stack — Master Logic Diagrams, Event Sequence Diagrams, event trees, fault trees, and minimal cut sets — for building or auditing PRA models. - Quantitative Methods: Bayesian parameter estimation, aleatory/epistemic uncertainty separation, common-cause failure models (Alpha Factor, beta-factor), human reliability analysis (THERP, CREAM, NARA, SPAR-H), software risk (CSRM), and physics-based stress-strength models. - Results & Importance Analysis: Uncertainty propagation via Latin Hypercube Sampling, importance measures (F-V, RAW, Birnbaum, DIM), and launch-abort modeling with worked examples. - Use Case: Ask the agent how to select an HRA method for a time-critical abort action, and it reads the relevant chapter to give a grounded answer with trade-offs. ## Quick Start Ask the agent to explain how to quantify common-cause failures in a redundant system using the nasa-pra skill.
