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ed-investigate
Cross-signal incident investigation workflow - from alert to root cause using events, patterns, logs, metrics, traces and pipeline history.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
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Cross-signal incident investigation workflow - from alert to root cause using events, patterns, logs, metrics, traces and pipeline history.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
AI Teammate - manage connectors (PagerDuty, Slack, GitHub, ...), update teammates (agents) and view teammate activity.
Pipelines - fleet management, config changes, version history, deployments and live capture.
Dashboards - create, update, inspect and validate metric dashboards from the CLI.
Metrics - discover metric names and run aggregation queries (timeseries and tables).
Monitors - create, manage, snooze and resolve Edge Delta monitors and alerts.
Primary Edge Delta CLI - edx commands, authentication, output formats and conventions.
| name | ed-investigate |
| description | Cross-signal incident investigation workflow - from alert to root cause using events, patterns, logs, metrics, traces and pipeline history. |
| metadata | {"version":"1.0.0","author":"edgedelta","repository":"https://github.com/edgedelta/agent-skills","tags":"edgedelta,incident,investigation,rca,oncall,debugging","alwaysApply":"false"} |
A structured workflow for investigating production incidents with edx.
Work top-down: events → patterns → logs/metrics/traces → change correlation.
The edx CLI must be installed and authenticated. See the ed-edx skill.
--from/--to
(ISO 8601: 2026-06-12T10:00:00.000Z).--lookback and
narrow once the onset is visible.edx events search --from <start> --to <end> --output table
edx events search -q 'event.domain:"Monitor"' --lookback 2h
Note affected services and event types. Monitor alerts carry the monitor ID:
edx monitors get <id> shows the exact condition.
edx patterns list --summary --from <start> --to <end>
edx patterns list --negative -q 'service.name:"<svc>"' --offset 24h
New or surging negative patterns are your primary suspects. Pull raw lines:
edx logs search -q '"<distinctive token from pattern>"' --from <start> --to <end>
edx logs graph -q 'severity_text:"ERROR"' --group-by service.name --lookback 6h
edx metrics query --name <latency/error metric> --agg avg --group-by service.name
Identify exactly when the regression started - this timestamp drives step 5.
edx service-map --lookback 1h
edx traces search -q 'status.code:"500" AND service.name:"<svc>"' --include-children
Find the deepest failing span: that service/dependency is the likely root cause; everything upstream is blast radius.
Root causes are usually changes. Check what changed right before onset:
edx pipelines history <pipeline-id> --output table --columns timestamp,author,status,description
edx fleet deployments
Compare change timestamps with the regression onset from step 3. Match the change content to the failure (e.g. live-capture errors → capture-related changes). Name the top offending change (top two if unsure) and say why.
edx pipelines deploy <pipeline-id> <last-good-version> --yes, then re-run the
step 3 graph to confirm recovery.edx capture start <pipeline-id> --nodes <node> --duration 2m.Summarize: window, affected services, the evidence chain (event → pattern → metric onset → failing span), the correlated change with author and timestamp, and the mitigation taken or proposed.