risk-distribution-fitter
Probability distribution fitting skill for calibrating uncertainty models from historical data or expert judgment
Profile →npx skills add a5c-ai/babysitter --skill risk-distribution-fitter --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Risk Distribution Fitter ## Overview The Risk Distribution Fitter skill provides capabilities for calibrating probability distributions from historical data or expert judgment. It supports both data-driven fitting using statistical methods and expert elicitation protocols for subjective probability assessment. ## Capabilities - Maximum likelihood estimation (MLE) - Method of moments estimation - Bayesian parameter estimation - Goodness-of-fit testing (KS, AD, Chi-square) - Distribution comparison and selection - Expert elicitation protocol support (3-point, 5-point) - PERT distribution calculation - Visualization of fitted distributions ## Used By Processes - Monte Carlo Simulation for Decision Support - Predictive Analytics Implementation - Decision Quality Assessment ## Usage ### Data-Driven Fitting ```python # Fit distributions to historical data fitting_config = { "data": [/* historical observations */], "candidate_distributions": [ "normal", "lognormal", "gamma", "weibull", "exponential", "beta", "triangular" ], "fitting_method": "mle", "selection_criterion": "AIC" } ``` ### Expert Elicitation ```python # 3-point estimate (PERT) expert_estimate = { "method": "PERT", "minimum
- Overview
- Capabilities
- Used By Processes
- Usage
- Data-Driven Fitting
- Expert Elicitation
- Supported Distributions
- Goodness-of-Fit Tests
- Model Selection Criteria
- Input Schema
- Output Schema
- Best Practices
- Expert Elicitation Guidelines
- Integration Points
What does the risk-distribution-fitter skill do?
Probability distribution fitting skill for calibrating uncertainty models from historical data or expert judgment
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill risk-distribution-fitter --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.