Individual skill
dowhy
Causal inference framework for answering "does X cause Y?" beyond correlation. DoWhy (Microsoft Research) provides the identify-estimate-refute loop: define a causal graph (DAG), identify the causal effect using backdoor/frontdoor/instrumental variable criteria, estimate treatment effects with multiple estimators, and validate results with automated refutation tests. Use when: distinguishing causation from correlation, estimating treatment effects (ATE, ATT, CATE), designing and analyzing A/B tests with confounders, using instrumental variables, performing counterfactual reasoning ("what would have happened if..."), validating causal claims with sensitivity analysis, working with observational data where randomization is impossible, or any analysis where the question is "what is the CAUSAL effect of X on Y" rather than just "how do X and Y relate?"
skills/63-tondevrel-scientific-agent-skills/dowhy/SKILL.md
Source commit 8684584e7d1127940f018157d2c579974fae8f79
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- Matches the observed repository HEAD
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- Observed behavior
- Network or broad shell
- Last checked
- Nov 10, 2026
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Repository context
- Repository stars (not skill ratings)
- 5,001
- Repository last updated
- Nov 9, 2026
- License
- NOASSERTION
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- academic-research Repository topic
- agent-skills Repository topic
- ai-agent Repository topic
- awesome-list Repository topic
- communication Repository topic
- economics Repository topic
- education Repository topic
- empirical-research Repository topic
- international-relations Repository topic
- political-science Repository topic
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