TraceRoot

TraceRoot is an open-source AI agent improvement platform. Find the patterns in your agent's production issues. Ship verified fixes with your coding agent. Instrument your code with a few lines, get full visibility into every LLM call, tool invocation, and agent decision. Run detectors to catch failures and hallucinations the moment they happen. Then let TraceRoot’s AI agent analyze findings, debug failures and create fix PRs automatically.

TraceRoot automatically detects failures and inefficiencies in production agent traffic, then clusters related judge outputs into improvement signals. Your coding agent uses the TraceRoot CLI to investigate those signals and make changes in a local worktree. Compare offline agent eval runs to verify the fix and catch regressions, then repeat the loop with new production traffic.

Detectors run online evaluations on production traces to identify failures and inefficiencies. Patterns across judge outputs surface as improvement signals. Offline agent evals then test your changes against datasets and compare results with a baseline to verify the fix and catch regressions.

TraceRoot CLI connects your coding agent to Home, traces, dashboards, detectors, evaluations, datasets, signals, and alerts. Connections are bidirectional except for traces, which point toward the agent. Read traces, signals, and workspace context; manage detectors, datasets, evals, dashboards, and alerts—all through an agent-native CLI.

Use cases

• Identify failures and improve agent reliability in production
• Automate debugging and PR creation for fixes