Liza is a disciplined multi-agent orchestration system for AI-assisted software development. It manages a pipeline of roles (orchestrator, coder, reviewer, architect) that collaborate via a behavioral contract enforced by deterministic Go code. The system provides a CLI (Cobra) and a Bubbletea TUI, with a YAML-based state file (blackboard) for persistence, Git worktree isolation per task, and a state-machine task lifecycle (planning → implementation → review → merge). It integrates with multiple LLM providers (Claude, Codex, Gemini, etc.) via their CLIs or the Agent Context Protocol (ACP). The architecture follows a clean layered design: `cmd/liza/` contains CLI commands, `internal/commands/` are thin adapters, `internal/ops/` holds core business logic (claiming, submitting, reviewing, merging, recovering), `internal/models/` defines domain types, and `internal/db/` manages the blackboard. The system is heavily test-covered with unit, integration, and lifecycle replay tests. It also includes optional codebase indexing via SCIP, Stacklit, and Semble for improved context. Key features include generation-fenced agent authority, circuit breaker anomaly detection, sprint metrics, checkpoint summaries, automated dependency repair, and pre-commit hooks. The repository is well-documented with extensive ADRs, architecture diagrams, and skill definitions. While the codebase is large and has some platform-specific code (Windows support), it demonstrates high craftsmanship in its use of idempotent lifecycle receipts, file-locking primitives, and error classification.