azure-ai-apps

Repo-specific guidance for implementing and modifying the agentframework/ project in azure-ai-apps. Covers existing ChatAgent patterns, config-driven agent selection, Kaito/Azure Foundry backends, diagnostics integration, SQLite vs Azure SQL handling, and targeted validation commands. WHEN: change agentframework, add agent to chatbot, add BaseChatClient backend, modify chatbot/config.yaml, update prompts, add diagnostics, change thread or memory handling, work on Kaito integration, work on Azure SQL fitness memory, update Streamlit chatbot behavior.

Best practices for creating modular, well-designed, robust, maintainable, and easy-to-read code. Covers decomposition, naming, boundaries, error handling, testing, observability, and practical implementation workflow. WHEN: refactor code, improve design, modularize code, simplify logic, reduce coupling, improve readability, add tests, review maintainability, clean up architecture, improve error handling, improve code quality, make code easier to understand, design new module, split large class, split large function, review robustness, make agent code maintainable.