skills/brycewang-stanford/auto-empirical-research-skills/Full-empirical-analysis-skill/Gen Agent Trust Hub
Full-empirical-analysis-skill
Pass
Audited by Gen Agent Trust Hub on Sep 2, 2026
Risk Level: SAFEEXTERNAL_DOWNLOADSCOMMAND_EXECUTIONINDIRECT_PROMPT_INJECTION
Full Analysis
- [EXTERNAL_DOWNLOADS]: The skill documentation recommends the installation of several standard Python libraries for data science, econometrics, and epidemiology, including
pandas,statsmodels,econml, andpyfixest. These are well-known packages hosted on official registries. - [COMMAND_EXECUTION]: The instructions include standard shell commands for skill installation (copying and symlinking files) and environment setup (pip installations). The core functionality involves the agent generating and executing Python scripts to perform statistical modeling and data visualization.
- [INDIRECT_PROMPT_INJECTION]: The skill defines a workflow for ingesting and processing untrusted external data files (e.g., CSV, Excel, Stata datasets) supplied by the user.
- Ingestion points: Data enters the agent's context through
pandas.read_*andpyreadstatfunctions in the cleaning and transformation scripts. - Boundary markers: The instructions do not currently include explicit boundary markers or warnings to the agent to ignore potential instructions embedded within the data values.
- Capability inventory: The skill has capabilities to write to the file system (saving tables and figures) and execute shell commands for package management and script execution.
- Sanitization: There is no explicit sanitization of data content; however, the data is primarily processed by mathematical and statistical libraries, which reduces the risk of direct execution of malicious payload strings.
Audit Metadata