Analyze the experiment precompute result-consistency canary across prod-US and prod-EU, deep-dive any issues, and produce an actionable report. Sweeps the canary's Prometheus health gauges in both regions, and when anything is unhealthy pulls the structured divergence/failure logs from Loki to reconstruct exactly which (team, experiment, metric) went wrong, by how much, and which class of divergence it is (stability vs correctness, and for correctness whether exposure counts or only values differ). Mechanism-level root cause needs ClickHouse and is out of scope — the skill hands off with precise drill-down steps. Use when the user asks to check / analyze / verify the experiment precompute canary, investigate a canary divergence or alert, or confirm precomputed experiment results are consistent in production. All data comes through the Grafana MCP (Prometheus + Loki) — no payload decryption, no ClickHouse.
76
94%
Does it follow best practices?
Run evals on this skill
Adds up to 20 points to the overall score
View guide
Low
Low-risk findings worth noting
This skill hasn't been evaluated yet
b0fece0
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.