Catch agent regressions
before users do.

Automated evaluation harness for AI agent runs. Measure completeness, correctness, and consistency across every execution cohort.

$ runharness eval --cohort baseline-002 --suite onboarding Running 8 quality checks across 5 agents... PASS email_delivery .......... 5/5 sent PASS landing_page_quality .... score 94/100 PASS task_creation ........... 3/3 valid FAIL mission_doc_depth ....... score 62/100 (threshold: 70) PASS tweet_format ............ compliant Results: 7/8 passed | 1 regression detected | cohort avg: 91.2
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Cohort-Based Evaluation

Run identical scenarios across agent cohorts. Compare outputs side-by-side. Detect drift before it compounds into user-facing failures.

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Layered Quality Scoring

Separate scoring for completeness, correctness, format compliance, and tone. Know exactly which layer regressed and why.

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Regression Gates

Set quality thresholds per evaluation dimension. Block deployments that drop below baseline. Automated CI/CD integration.

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Execution Tracing

Full trace replay for every agent run. See tool calls, model responses, and decision points. Debug failures in minutes, not hours.

Built for scale

Quality infrastructure that keeps pace with your agent fleet.

8
Quality dimensions scored
<2s
Evaluation latency
100%
Execution coverage
N+1
Cohort comparisons

Every agent run measured. Every regression caught.

Quality isn't optional when your agents run autonomously. RunHarness makes it automatic.