Generate data specifications, Jupyter notebooks, and Streamlit dashboards from natural language descriptions. Evaluate AI-powered data systems against Responsible AI standards. This collection includes specialized agents for data science workflows in Python and RAI assessment.

> [!CAUTION]
> The RAI agents and prompts in this collection are **assistive tools only**. They do not replace qualified human review, organizational RAI review boards, or regulatory compliance programs. All AI-generated RAI artifacts **must** be reviewed and validated by qualified professionals before use. AI outputs may contain inaccuracies, miss critical risks, or produce recommendations that are incomplete or inappropriate for your context.

This collection includes agents for:

- **Data Specification Generation** — Create structured data schemas and specifications from requirements
- **Jupyter Notebook Generation** — Build data analysis notebooks with visualizations and documentation
- **Streamlit Dashboard Generation** — Create interactive dashboards from data sources
- **Dashboard Testing** — Comprehensive test suites for Streamlit applications
- **RAI Planner** — Responsible AI assessment with security model analysis, impact assessment, and dual-format backlog handoff

This collection includes prompts for:

- **Synthetic Data Generation** — Generate comprehensive synthetic datasets with realistic patterns, relationships, and statistical comparisons against optional reference data
