Rudel

Rudel collects and visualizes usage data from Claude Code and Codex sessions, giving development teams insight into how their AI coding agents are employed. It records metrics such as session duration, frequency, and command patterns, then aggregates the information into dashboards that can be filtered by user, project, or time period. The tool is intended for teams that rely on Claude Code or Codex for code generation and want to monitor adoption, identify bottlenecks, and assess overall productivity.

The analytics focus on raw interaction logs, presenting counts of prompts, responses, and token usage without altering the underlying code. By exposing these figures, Rudel helps engineers and managers understand which features are most utilized and where training or policy adjustments may be needed. The system is designed to be integrated into existing development workflows, pulling data from the AI agents’ APIs and storing it for later review.

Rudel is positioned as an experimental utility for organizations seeking transparent, data‑driven oversight of AI‑assisted coding activities. Its primary value lies in turning opaque session activity into actionable metrics that can be shared across a development team.