Show HN: Causal analyst agent skill for Claude (github.com)

A new Agent Skill for Claude has been introduced that simplifies causal analysis for non-data scientists, enabling users to investigate whether one factor truly causes another using their business data. By allowing domain experts to ask questions like "Did our loyalty program actually raise monthly spend?" Claude handles complex modeling and provides a comprehensive one-page report that outlines findings, trust grades, and any limitations in the data. This innovative tool addresses the frequent disconnect between domain knowledge and data science expertise, enabling quicker and more effective decision-making without the usual back-and-forth communication. The significance of this development lies in its potential to democratize causal analysis, making it accessible to professionals without advanced statistical backgrounds. By structuring the workflow to ensure transparency in judgments and decision-making, this skill minimizes the chance of incorrect conclusions and provides a clear audit trail for findings. Key features include diagnostics for assessing data integrity, adjustments for biases, and explicit uncertainty grading, which collectively enhance the robustness of the analysis. This flood of safeguards enables organizations to derive actionable insights while clearly acknowledging the limits of their data, fundamentally transforming how businesses can leverage data-driven decision-making.