npx skills add a5c-ai/babysitter --skill robust-statistics-toolkit --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.
# Robust Statistics Toolkit ## Purpose Provides robust statistical methods resistant to outliers and model violations for reliable inference. ## Capabilities - M-estimators (Huber, Tukey) - Trimmed and winsorized estimators - Robust regression (MM-estimation) - Breakdown point analysis - Influence function computation - Robust covariance estimation ## Usage Guidelines 1. **Outlier Detection**: Identify potential outliers first 2. **Estimator Selection**: Choose based on expected contamination 3. **Breakdown Point**: Consider required breakdown point 4. **Efficiency**: Balance robustness and efficiency ## Tools/Libraries - robustbase (R) - scikit-learn - statsmodels
- Purpose
- Capabilities
- Usage Guidelines
- Tools/Libraries
What does the robust-statistics-toolkit skill do?
Robust statistical methods resistant to outliers
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill robust-statistics-toolkit --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.