Monitors and manages agent loops across multiple repositories with real-time status tracking and crash detection.
Agent Loop Observer provides comprehensive observability for AI agent loops, allowing users to track running, completed, and crashed tasks across all local repositories from a single interface. By aggregating data from cross-repo registries, per-repo tracking logs, and Git-committed history, it offers a centralized view of agent activity including iteration counts, stop reasons, and tmux session management. This skill is essential for developers running background AI tasks who need to verify progress, troubleshoot failures, or quickly re-attach to active terminal sessions.
Características Principales
01Automatic detection and reporting of crashed loops with synthetic event logging
02Real-time monitoring of running loops with tmux session integration
03Cross-repository visibility of all active and historical agent loops
04Detailed iteration timelines showing worker and reviewer performance metrics
05Advanced filtering by repository, branch, date, or stop reason
061 GitHub stars
Casos de Uso
01Re-attaching to a specific agent's terminal session using provided tmux commands
02Debugging a failed agent loop by reviewing iteration-level logs and stop reasons
03Auditing multiple background AI agent tasks to see which are currently active
