causal-inference-engine
Causal inference skill for estimating treatment effects and understanding causal relationships in business data
npx skills add a5c-ai/babysitter --skill causal-inference-engine --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.
# Causal Inference Engine ## Overview The Causal Inference Engine skill provides sophisticated methods for estimating causal effects from observational data. It enables business analysts to move beyond correlation to understand true cause-and-effect relationships, supporting evidence-based decision-making for interventions, policy changes, and strategic initiatives. ## Capabilities - Propensity score matching - Inverse probability weighting - Difference-in-differences - Instrumental variables - Regression discontinuity - Synthetic control methods - Causal forest implementation - Sensitivity analysis to unobserved confounding ## Used By Processes - A/B Testing and Experimentation Framework - Predictive Analytics Implementation - Win/Loss Analysis Program ## Usage ### Problem Definition ```python # Define causal question causal_problem = { "treatment": "marketing_campaign", "outcome": "purchase_conversion", "confounders": ["customer_segment", "prior_purchases", "channel", "region"], "instruments": ["random_assignment_probability"], # if available "effect_type": "ATE", # Average Treatment Effect "heterogeneity": ["customer_segment", "tenure"] # for CATE } ``` ### Propensity Score Matc
- Overview
- Capabilities
- Used By Processes
- Usage
- Problem Definition
- Propensity Score Matching
- Difference-in-Differences
- Causal Forest (Heterogeneous Effects)
- Method Selection Guide
- Input Schema
- Output Schema
- Best Practices
- Refutation Tests
- Integration Points
What does the causal-inference-engine skill do?
Causal inference skill for estimating treatment effects and understanding causal relationships in business data
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill causal-inference-engine --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.