Causal DAG Development

This skill empowers researchers to translate complex theoretical frameworks and narratives into rigorous causal diagrams. It guides users through a multi-phase workflow—from initial conceptual mapping to identification auditing using d-separation rules—ensuring that causal assumptions are explicit and valid. Once a DAG is finalized, the skill automates the generation of professional, publication-quality figures using Mermaid, R (ggdag), or Python (networkx), streamlining the path from social science theory to high-fidelity visual assets for papers and presentations.

主な機能

ユースケース