bot-framework

What problem does it solve?

This Skill eliminates the need for developers to manually sift through scattered codebase documentation to understand the Swiss AI Hub bot integration framework's complex architecture, multi-channel handling logic, and production-grade patterns, reducing onboarding time and debugging effort for bot-related tasks.

Core Features & Use Cases

• Full Architecture Reference: Covers the three-layer bot architecture (BaseChatBot, specialized bots, streaming variants), CompletionHandler strategy pattern, and end-to-end request flow from Azure Bot Service to agent response.
• Multi-Channel Implementation Guidance: Includes detailed documentation for Teams, Slack, and WebChat handling, including Slack thread formatting, Teams conversation reuse logic, mention detection, and channel-specific edge cases.
• BITL & State Management: Documents Bot-in-the-Loop (BITL) flows for human-in-the-loop agent workflows, conversation TTL configuration, MongoDB-backed conversation state tracking, and NATS event integration for agent communication.
• Use Case: For example, a developer building a Slack integration for Swiss AI Hub agents can use this Skill to correctly implement thread handling and @mention logic, while an engineer debugging streaming response issues can reference the typing indicator lifecycle and CloudAdapter caching behavior to resolve problems quickly.

Quick Start

Use the bot-framework skill to explain how the CompletionHandler pattern routes messages between Slack channels and NATS-connected agents.