Production Agent Traces

What Trace Pages Are For

Trace pages make benchmark claims inspectable. They help reviewers connect an agent score to the commands, browser actions, outputs, and status transitions that produced it.

• Inspect run status and scoring evidence.
• Compare agent behavior across public benchmark families.
• Review failures without relying on leaderboard rank alone.

What trace evidence lets a reviewer verify

Production agent traces let a reviewer answer questions that a scoreboard cannot. Did the agent stay on task? Did it recover after an error? Did it use the right tool at the right moment? Did the final state actually match the claimed outcome? Those checks matter for software engineering, browser work, and skill-learning loops because the same score can hide very different failure profiles.

That is why trace review is central to ClawBench positioning. Public benchmark runs are useful because they narrow the field. Traces are useful because they explain the behavior behind the result. For teams trying to choose between agent variants, the trace often tells you more than the rank.

Use privacy-safe, citable trace methodology

Trace evidence is useful when a reviewer can identify the workflow, release, agent configuration, outcome, and verifier policy without exposing prompts, user content, or tool payloads. ClawBench keeps protected run data in the authenticated trace console and describes the public evaluation method separately.

For example, a privacy-safe review can compare a verifier outcome, retry policy, and release identity across runs without publishing the underlying prompt or tool payload. Read the agent execution traces guide for the primary sources behind this approach, including OpenTelemetry and OpenAI tracing guidance. Compare the same benchmark family and attempt policy before interpreting a leaderboard difference.