skills/brycewang-stanford/auto-empirical-research-skills/Full-empirical-analysis-skill-R/Gen Agent Trust Hub
Full-empirical-analysis-skill-R
Pass
Audited by Gen Agent Trust Hub on Jun 1, 2026
Risk Level: SAFE
Full Analysis
- [SAFE]: The skill defines a structured workflow for data analysis in R. It focuses on well-known econometric methods such as Difference-in-Differences (DID), Instrumental Variables (IV), and Regression Discontinuity (RD).
- [SAFE]: No malicious patterns such as prompt injection, data exfiltration, or obfuscation were detected. The skill promotes security best practices by incorporating data validation and sample construction logging.
- [SAFE]: All listed R package dependencies (e.g., tidyverse, fixest, did, DoubleML) are legitimate, well-maintained libraries from the Comprehensive R Archive Network (CRAN) or established research organizations.
- [SAFE]: The skill's instructions for file operations (reading data and writing tables/figures) are transparent and limited to the project workspace, consistent with its primary purpose of empirical research.
Audit Metadata