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# Data Science

Data specification generation, Jupyter notebooks, and Streamlit dashboards

> [!CAUTION]
> This collection includes RAI (Responsible AI) agents and prompts that are **assistive tools only**. They do not replace qualified responsible AI review, ethics board oversight, or established organizational RAI governance processes. All AI-generated RAI assessments, impact analyses, and recommendations **must** be reviewed and validated by qualified professionals before use. AI outputs may contain inaccuracies, miss critical risk categories, or produce recommendations that are incomplete or inappropriate for your context.

## Overview

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.

<!-- BEGIN AUTO-GENERATED ARTIFACTS -->

### Chat Agents

| Name                         | Description                                                                                                                                                                                                                                                 |
|------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| **gen-data-spec**            | Generate comprehensive data dictionaries, machine-readable data profiles, and objective summaries for downstream analysis (EDA notebooks, dashboards) through guided discovery                                                                              |
| **gen-jupyter-notebook**     | Create structured exploratory data analysis Jupyter notebooks from available data sources and generated data dictionaries                                                                                                                                   |
| **gen-streamlit-dashboard**  | Develop a multi-page Streamlit dashboard                                                                                                                                                                                                                    |
| **rai-planner**              | Responsible AI assessment agent with 5-phase conversational workflow. Evaluates AI systems against Microsoft RAI Standard v2 and NIST AI RMF 1.0. Produces RAI security model, impact assessment, control surface catalog, and dual-format backlog handoff. |
| **researcher-subagent**      | Research subagent using search tools, read tools, fetch web page, github repo, and mcp tools                                                                                                                                                                |
| **test-streamlit-dashboard** | Automated testing for Streamlit dashboards using Playwright with issue tracking and reporting                                                                                                                                                               |

### Prompts

| Name                            | Description                                                                                                                              |
|---------------------------------|------------------------------------------------------------------------------------------------------------------------------------------|
| **rai-capture**                 | Initiate a responsible AI assessment from existing knowledge using the RAI Planner agent in capture mode                                 |
| **rai-plan-from-prd**           | Initiate a responsible AI assessment from PRD/BRD artifacts using the RAI Planner agent in from-prd mode                                 |
| **rai-plan-from-security-plan** | Initiate a responsible AI assessment from a completed Security Plan using the RAI Planner agent in from-security-plan mode (recommended) |
| **synth-data-generate**         | Generate comprehensive synthetic data for any specified subject with realistic patterns and relationships                                |

### Instructions

| Name                                   | Description                                                                                                                                                                                                                                                 |
|----------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| **coding-standards/python-script**     | Instructions for Python scripting implementation                                                                                                                                                                                                            |
| **coding-standards/uv-projects**       | Create and manage Python virtual environments using uv commands                                                                                                                                                                                             |
| **rai-planning/rai-backlog-handoff**   | RAI review and backlog handoff for Phase 6: review rubric, RAI scorecard, dual-format backlog generation                                                                                                                                                    |
| **rai-planning/rai-capture-coaching**  | Exploration-first questioning techniques for RAI capture mode adapted from Design Thinking research methods                                                                                                                                                 |
| **rai-planning/rai-identity**          | RAI Planner identity, 5-phase orchestration, state management, and session recovery                                                                                                                                                                         |
| **rai-planning/rai-impact-assessment** | RAI impact assessment for Phase 5: control surface taxonomy, evidence register, tradeoff documentation, and work item generation                                                                                                                            |
| **rai-planning/rai-security-model**    | RAI security model analysis for Phase 4: AI STRIDE extensions, dual threat IDs, ML STRIDE matrix, and security model merge protocol                                                                                                                         |
| **rai-planning/rai-standards**         | Embedded RAI standards for Phase 3: Microsoft RAI Standard v2 principles and NIST AI RMF subcategory mappings                                                                                                                                               |
| **shared/hve-core-location**           | Important: hve-core is the repository containing this instruction file; Guidance: if a referenced prompt, instructions, agent, or script is missing in the current directory, fall back to this hve-core location by walking up this file's directory tree. |

<!-- END AUTO-GENERATED ARTIFACTS -->

## Install

```bash
copilot plugin install data-science@hve-core
```

## Agents

| Agent                    | Description                                                                                                                                                                                                                                                                                        |
|--------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| gen-data-spec            | Generate comprehensive data dictionaries, machine-readable data profiles, and objective summaries for downstream analysis (EDA notebooks, dashboards) through guided discovery                                                                                                                     |
| gen-jupyter-notebook     | Create structured exploratory data analysis Jupyter notebooks from available data sources and generated data dictionaries                                                                                                                                                                          |
| gen-streamlit-dashboard  | Develop a multi-page Streamlit dashboard                                                                                                                                                                                                                                                           |
| test-streamlit-dashboard | Automated testing for Streamlit dashboards using Playwright with issue tracking and reporting                                                                                                                                                                                                      |
| rai-planner              | Responsible AI assessment agent with 5-phase conversational workflow. Evaluates AI systems against Microsoft RAI Standard v2 and NIST AI RMF 1.0. Produces RAI security model, impact assessment, control surface catalog, and dual-format backlog handoff. - Brought to you by microsoft/hve-core |
| researcher-subagent      | Research subagent using search tools, read tools, fetch web page, github repo, and mcp tools                                                                                                                                                                                                       |

## Commands

| Command                     | Description                                                                                                                              |
|-----------------------------|------------------------------------------------------------------------------------------------------------------------------------------|
| rai-capture                 | Initiate a responsible AI assessment from existing knowledge using the RAI Planner agent in capture mode                                 |
| rai-plan-from-prd           | Initiate a responsible AI assessment from PRD/BRD artifacts using the RAI Planner agent in from-prd mode                                 |
| rai-plan-from-security-plan | Initiate a responsible AI assessment from a completed Security Plan using the RAI Planner agent in from-security-plan mode (recommended) |
| synth-data-generate         | Generate comprehensive synthetic data for any specified subject with realistic patterns and relationships                                |

## Instructions

| Instruction                        | Description                                                                                                                                                                                                                                                 |
|------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| python-script.instructions         | Instructions for Python scripting implementation - Brought to you by microsoft/hve-core                                                                                                                                                                     |
| uv-projects.instructions           | Create and manage Python virtual environments using uv commands                                                                                                                                                                                             |
| rai-backlog-handoff.instructions   | RAI review and backlog handoff for Phase 6: review rubric, RAI scorecard, dual-format backlog generation                                                                                                                                                    |
| rai-identity.instructions          | RAI Planner identity, 5-phase orchestration, state management, and session recovery - Brought to you by microsoft/hve-core                                                                                                                                  |
| rai-impact-assessment.instructions | RAI impact assessment for Phase 5: control surface taxonomy, evidence register, tradeoff documentation, and work item generation                                                                                                                            |
| rai-security-model.instructions    | RAI security model analysis for Phase 4: AI STRIDE extensions, dual threat IDs, ML STRIDE matrix, and security model merge protocol                                                                                                                         |
| rai-standards.instructions         | Embedded RAI standards for Phase 3: Microsoft RAI Standard v2 principles and NIST AI RMF subcategory mappings                                                                                                                                               |
| rai-capture-coaching.instructions  | Exploration-first questioning techniques for RAI capture mode adapted from Design Thinking research methods - Brought to you by microsoft/hve-core                                                                                                          |
| hve-core-location.instructions     | Important: hve-core is the repository containing this instruction file; Guidance: if a referenced prompt, instructions, agent, or script is missing in the current directory, fall back to this hve-core location by walking up this file's directory tree. |

---

> Source: [microsoft/hve-core](https://github.com/microsoft/hve-core)

