Repair An Agent From Trace Evidence

Before You Start#

You need:

• a project with diagnosis-ready trace evidence;
• at least one enabled diagnostic Rule;
• a GitHub, GitLab, Linear, or Jira connector for external handoff.

Complete the Quickstart first if no traces are visible.

1. Reproduce A Representative Failure#

Run a real agent task that exhibits the behavior you want to correct. Prefer one complete user goal over an artificial isolated model call.

Open Traces and verify that the trajectory includes the relevant prompt, model, tool, result, and final-answer evidence.

2. Run Diagnostics#

Open Findings and enable Auto-diagnose for future conversations. To process existing evidence, run an enabled Rule against a selected time window.

A completed Rule Run does not always produce a Finding. Healthy conversations and candidates below the configured signal or confidence thresholds are intentionally excluded.

3. Review The Finding#

Confirm that the Finding contains:

• the failure mechanism rather than only a symptom;
• trace or span evidence that supports the claim;
• an appropriate severity and confidence;
• a repair direction narrow enough to implement and verify.

Confirm actionable Findings and dismiss unsupported ones. See Findings for the complete review lifecycle.

4. Hand Off The Repair#

Configure an issue-system connector, then create a work item from the Finding. Provon includes the goal, cause assessment, evidence, remediation direction, and correlation metadata.

Repository access remains with the user-controlled development workflow. Provon does not check out the repository or apply code changes.

See Repair handoff and connectors.

5. Verify The Outcome#

After the change is deployed, inspect new traces for the same behavior. A later occurrence can reopen a resolved Finding as a regression; absence of new evidence should not be treated as proof that the repair worked.

For local or CI-oriented diagnosis without persisting Findings, use CLI diagnosis.