dag-development

What problem does it solve?

This skill helps researchers convert their research questions and literature into explicit causal diagrams (DAGs) and render publication-ready figures using Mermaid, R, or Python, ensuring transparent causal assumptions and reproducible visuals.

Core Features & Use Cases

• DAG translation: turn theory or core papers into explicit DAGs with nodes and edges.
• Phase-driven workflow: supports the full DAG lifecycle from Phase 0 theory to Phase 5 rendering (Mermaid, R, Python).
• Publication-ready visuals: export clean diagrams in SVG/PNG/PDF for papers, slides, or appendices.
• Use Case: a social-science researcher translates a theory into a DAG, audits it for backdoor paths, then renders figures for a manuscript.

Quick Start

Provide a Phase 0 DAG blueprint by translating your causal question into nodes and edges, then render phase outputs using Mermaid, R, or Python.