Orchestration & Protocols

These packages give you a complete lifecycle for transferring a conversation from one AI agent to another mid-session, including compressing the conversation history, scoring and selecting the best target agent, validating payload compatibility, delivering the handoff via MCP or A2A transport, and handling rejection with fallback alternatives. You would adopt them to solve the problem of routing a live multi-turn conversation between specialized agents without losing context or requiring the user to repeat themselves. The most distinctive thing is that every stage—compression, routing, validation, transport, and rejection handling—is a separate, pluggable package with zero runtime dependencies, so you can compose only the pieces you need and inject your own implementations for any stage.

These packages give you a complete multi-agent orchestrator that routes user requests to the right agent based on intent confidence, manages multi-turn sessions, and isolates failing agents with circuit breakers. You would adopt them to build a production system where multiple specialized AI agents handle different tasks (like password resets, HR queries, or IT support) behind a single API endpoint, with automatic fallback and clarification when the intent is unclear. The most distinctive thing is how the packages compose around a confidence-gated decision tree—Gemini Flash classifies intent, a 5-rule engine decides whether to route, clarify, or fall back, and per-agent circuit breakers with Firestore persistence prevent cascading failures across Cloud Run instances.

These packages give you a config-driven LLM routing engine that selects models based on cost, latency, capability, or a two-tier judgment strategy, with automatic fallback chains and circuit breakers when models fail. You would adopt them to manage multi-provider LLM costs, enforce daily budgets, and add structured degradation paths without writing provider-specific orchestration code. The system is built as a set of independent packages—core types, engine, strategies, fallback, telemetry, MCP server, and CLI—that compose through a shared config schema and a single `executeModel` callback, keeping provider SDKs out of the router itself.