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Correlate query stats, telemetry, policy decisions, and replay memory into deterministic incident hypotheses and next-best actions.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Designs dry-run experiments across query rewrites, indexes, workload twins, and rollout gates.
Produces a board-level briefing for closed-loop autonomous database operations.
Enforces closed-loop dry-run boundaries and blocks autonomous production apply.
Scores whether enough evidence exists to recommend, defer, or escalate an autonomous operator decision.
Compares do-nothing, dry-run-change, rollback, and defer scenarios for an operating objective.
Builds an executive-grade decision evidence packet from runtime signals and confidence checks.
| name | ai-anomaly-triage |
| description | Correlate query stats, telemetry, policy decisions, and replay memory into deterministic incident hypotheses and next-best actions. |
Use this skill when an operator asks why database behavior changed, whether a deployment caused a regression, or what to investigate first during an incident.
Run:
node runtime/runTool.js ai_anomaly_triage '{"engine":"postgres","database":"analytics","deploymentId":"deploy-42","incidentWindowMinutes":45}'
The tool is offline and deterministic. It combines workload stats, telemetry-correlation output, policy-memory signals, and recent replay context. It returns an anomaly score, root-cause hypotheses, next-best actions, and explainability fields listing the exact signal families used.