Enables multi-model code review by fanning out issues to multiple LLMs simultaneously, diffing their unique insights, optionally running debate rounds, and dispatching subagents to implement fixes with git commits.
A lightweight coordination layer for multiple AI agents working on the same codebase, providing check-in and check-out tools via STDIO or Streamable HTTP.
A coordination layer for coding agents that provides memorable identities, inbox/outbox messaging, searchable message history, and file lease management to prevent conflicts. Uses Git for human-auditable artifacts and SQLite for fast queries, enabling multiple agents to collaborate across projects without stepping on each other.
Enables orchestration of multiple Jules AI workers for tasks like code generation, bug fixing, and review using the Google Jules API. It features git integration, a shared memory system, and real-time activity monitoring for complex, multi-agent development workflows.
An append-only coordination memory for multi-agent and human work, backed by SQLite, with a local dashboard and acceptance contracts that enforce integrator review before work is considered accepted.