Auto-Empirical-Research-Skills is a curated skills library for AI agents conducting empirical research across social science disciplines.
The project addresses the challenge of automating empirical research workflows by providing a structured collection of reusable agent skills organized across economics, education, political science, psychology, public administration, international relations, sociology, and communication. These skills enable AI agents to execute research tasks systematically, from data preparation through statistical analysis and paper generation. The approach centers on skill modularity and discipline-specific organization, allowing agents to compose research workflows by selecting and chaining appropriate skills for their research questions.
Researchers and teams automating empirical studies should consider this library if they work within the covered social science disciplines and want to reduce manual implementation of standard research procedures. The tool suits projects requiring reproducible research workflows and those seeking to accelerate the transition from research design to executable analysis pipelines. It is particularly relevant for teams building AI-assisted research platforms or those integrating empirical research capabilities into agent-based systems.
The project maintains an active codebase with regular updates to the skills collection and documentation. Development activity shows ongoing refinement of the library structure and expansion of discipline coverage. The repository accepts community contributions, enabling users to upload and share custom skills alongside the curated collection.
