Babysitter causal-inference-engine

Causal reasoning implementing DAG construction, do-calculus, and intervention effect estimation

install

source · Clone the upstream repo

git clone https://github.com/a5c-ai/babysitter

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/domains/science/scientific-discovery/skills/causal-inference-engine" ~/.claude/skills/a5c-ai-babysitter-causal-inference-engine-92b5a1 && rm -rf "$T"

manifest: library/specializations/domains/science/scientific-discovery/skills/causal-inference-engine/SKILL.md

Causal Inference Engine

Purpose

Provides causal reasoning capabilities implementing DAG construction, do-calculus, and intervention effect estimation.

Capabilities

Causal DAG construction and validation
Backdoor/frontdoor criterion checking
Average treatment effect estimation
Instrumental variable analysis
Mediation analysis
Sensitivity analysis for unmeasured confounding

Usage Guidelines

DAG Construction: Build causal graphs from domain knowledge
Identification: Check if effects are identifiable
Estimation: Apply appropriate estimation methods
Sensitivity: Assess robustness to unmeasured confounding

Tools/Libraries

DoWhy
CausalNex
pgmpy
EconML