What it measures
Agents investigate Kubernetes incidents from offline snapshots of telemetry and system structure.
How to read the result
Look for correct contributing entities and a causal explanation supported by the observed system evidence.
Limits and comparison traps
This AA variant diagnoses snapshots. It should not be described as a live remediation or production incident-response benchmark.
Benchmark reference notes
Kubernetes site-reliability incident root-cause analysis from alerts, traces, events, and network topology snapshots.
Where this fits in an evaluation suite
A transcript that says “done” is weaker evidence than the verified final state. Track policy violations, recoveries, and invalid attempts alongside success.
Start with a capability hypothesis, then choose a second test with a different failure mode. Keep the checkpoint, reasoning effort, agent tools, sampling policy, and scoring procedure fixed when measuring a training intervention. Record failures and missing outputs in the denominator.
A reproducible comparison
Use the exact implementation, version, task subset, tool access, attempt budget, and judge described by the source.
Publish the exact run configuration, item coverage, score units, and available uncertainty. If a source supplies only an aggregate or a single run, preserve that limit. A new model name or a rounded score alone does not establish a capability improvement.
PRIMARY EVIDENCE & FURTHER READING
Reviewed 2026-10-26. Explanation and interpretation by RLTasks. Benchmark ownership remains with its original authors.