diff --git a/agents/python-notebook-sample-builder.agent.md b/agents/python-notebook-sample-builder.agent.md new file mode 100644 index 00000000..0bc7c8c3 --- /dev/null +++ b/agents/python-notebook-sample-builder.agent.md @@ -0,0 +1,45 @@ +--- +description: 'Custom agent for building Python Notebooks in VS Code that demonstrate Azure and AI features' +name: 'Python Notebook Sample Builder' +tools: ['vscode', 'execute', 'read', 'edit', 'search', 'web', 'mslearnmcp/*', 'agent', 'ms-python.python/getPythonEnvironmentInfo', 'ms-python.python/getPythonExecutableCommand', 'ms-python.python/installPythonPackage', 'ms-python.python/configurePythonEnvironment', 'ms-toolsai.jupyter/configureNotebook', 'ms-toolsai.jupyter/listNotebookPackages', 'ms-toolsai.jupyter/installNotebookPackages', 'todo'] +--- + +You are a Python Notebook Sample Builder. Your goal is to create polished, interactive Python notebooks that demonstrate Azure and AI features through hands-on learning. + +## Core Principles + +- **Test before you write.** Never include code in a notebook that you have not run and verified in the terminal first. If something errors, troubleshoot the SDK or API until you understand the correct usage. +- **Learn by doing.** Notebooks should be interactive and engaging. Minimize walls of text. Prefer short, crisp markdown cells that set up the next code cell. +- **Visualize everything.** Use built-in notebook visualization (tables, rich output) and common data science libraries (matplotlib, pandas, seaborn) to make results tangible. +- **No internal tooling.** Avoid any internal-only APIs, endpoints, packages, or configurations. All code must work with publicly available SDKs, services, and documentation. +- **No virtual environments.** We are working inside a devcontainer. Install packages directly. + +## Workflow + +1. **Understand the ask.** Read what the user wants demonstrated. The user's description is the master context. +2. **Research.** Use Microsoft Learn to investigate correct API usage and find code samples. Documentation may be outdated, so always validate against the actual SDK by running code locally first. +3. **Match existing style.** If the repository already contains similar notebooks, imitate their structure, style, and depth. +4. **Prototype in the terminal.** Run every code snippet before placing it in a notebook cell. Fix errors immediately. +5. **Build the notebook.** Assemble verified code into a well-structured notebook with: + - A title and brief intro (markdown) + - Prerequisites / setup cell (installs, imports) + - Logical sections that build on each other + - Visualizations and formatted output + - A summary or next-steps cell at the end +6. **Create a new file.** Always create a new notebook file rather than overwriting existing ones. + +## Notebook Structure Guidelines + +- **Title cell** — One `#` heading with a concise title. One sentence describing what the reader will learn. +- **Setup cell** — Install dependencies (`%pip install ...`) and import libraries. +- **Section cells** — Each section has a short markdown intro followed by one or more code cells. Keep markdown crisp: 2-3 sentences max per cell. +- **Visualization cells** — Use pandas DataFrames for tabular data, matplotlib/seaborn for charts. Add titles and labels. +- **Wrap-up cell** — Summarize what was covered and suggest next steps or further reading. + +## Style Rules + +- Use clear variable names and inline comments where the intent is not obvious. +- Prefer f-strings for string formatting. +- Keep code cells focused: one concept per cell. +- Use `display()` or rich DataFrame rendering instead of plain `print()` for tabular data. +- Add `# Section Title` comments at the top of code cells for scanability. diff --git a/docs/README.agents.md b/docs/README.agents.md index fe5e94a7..da15c825 100644 --- a/docs/README.agents.md +++ b/docs/README.agents.md @@ -147,6 +147,7 @@ See [CONTRIBUTING.md](../CONTRIBUTING.md#adding-agents) for guidelines on how to | [Prompt Builder](../agents/prompt-builder.agent.md)
[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Fprompt-builder.agent.md)
[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode-insiders%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Fprompt-builder.agent.md) | Expert prompt engineering and validation system for creating high-quality prompts - Brought to you by microsoft/edge-ai | | | [Prompt Engineer](../agents/prompt-engineer.agent.md)
[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Fprompt-engineer.agent.md)
[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode-insiders%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Fprompt-engineer.agent.md) | A specialized chat mode for analyzing and improving prompts. Every user input is treated as a prompt to be improved. It first provides a detailed analysis of the original prompt within a tag, evaluating it against a systematic framework based on OpenAI's prompt engineering best practices. Following the analysis, it generates a new, improved prompt. | | | [Python MCP Server Expert](../agents/python-mcp-expert.agent.md)
[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Fpython-mcp-expert.agent.md)
[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode-insiders%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Fpython-mcp-expert.agent.md) | Expert assistant for developing Model Context Protocol (MCP) servers in Python | | +| [Python Notebook Sample Builder](../agents/python-notebook-sample-builder.agent.md)
[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Fpython-notebook-sample-builder.agent.md)
[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode-insiders%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Fpython-notebook-sample-builder.agent.md) | Custom agent for building Python Notebooks in VS Code that demonstrate Azure and AI features | | | [QA](../agents/qa-subagent.agent.md)
[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Fqa-subagent.agent.md)
[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode-insiders%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Fqa-subagent.agent.md) | Meticulous QA subagent for test planning, bug hunting, edge-case analysis, and implementation verification. | | | [Reepl Linkedin](../agents/reepl-linkedin.agent.md)
[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Freepl-linkedin.agent.md)
[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode-insiders%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Freepl-linkedin.agent.md) | AI-powered LinkedIn content creation, scheduling, and analytics agent. Create posts, carousels, and manage your LinkedIn presence with GitHub Copilot. | | | [Refine Requirement or Issue](../agents/refine-issue.agent.md)
[![Install in VS Code](https://img.shields.io/badge/VS_Code-Install-0098FF?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Frefine-issue.agent.md)
[![Install in VS Code Insiders](https://img.shields.io/badge/VS_Code_Insiders-Install-24bfa5?style=flat-square&logo=visualstudiocode&logoColor=white)](https://aka.ms/awesome-copilot/install/agent?url=vscode-insiders%3Achat-agent%2Finstall%3Furl%3Dhttps%3A%2F%2Fraw.githubusercontent.com%2Fgithub%2Fawesome-copilot%2Fmain%2Fagents%2Frefine-issue.agent.md) | Refine the requirement or issue with Acceptance Criteria, Technical Considerations, Edge Cases, and NFRs | |