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Use when incidents occur and you need to triage, categorize, and execute response runbooks automatically. Correlates alerts, identifies root causes, escalates to appropriate teams, and executes remediation procedures for production incidents.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | incident-triage-runbook |
| description | Use when incidents occur and you need to triage, categorize, and execute response runbooks automatically. Correlates alerts, identifies root causes, escalates to appropriate teams, and executes remediation procedures for production incidents. |
| license | AGPLv3 |
| metadata | {"author":"agentic-reconciliation-engine","version":"1.0","category":"enterprise","risk_level":"medium","autonomy":"conditional","layer":"temporal"} |
| compatibility | Requires Python 3.8+, cloud provider CLI tools (AWS CLI, Azure CLI, gcloud), and access to multi-cloud monitoring systems |
| allowed-tools | Bash Read Write Grep |
Enterprise-grade automation solution for incident triage runbook operations across AWS, Azure, GCP, and on-premise environments to maximize operational efficiency while maintaining security and compliance standards.
aws|azure|gcp|onprem|all (optional, default: all)production)true)core/scripts/automation/incident-triage-runbook.py: Main automation implementationcore/scripts/automation/incident-triage-runbook_handler.py: Cloud-specific operationscore/scripts/automation/multi_cloud_orchestrator.py: Cross-provider coordinationincident, triage, runbook, automation, enterprise, multi-cloud, aws, azure, gcp, onprem
Load these files when needed:
scripts/incident-triager.py - Alert correlation and categorization enginescripts/runbook-executor.py - Automated runbook execution frameworkreferences/incident-taxonomy.md - Standard incident classification systemassets/escalation-policies.yaml - Team escalation rules and contactsexamples/incident-scenarios/ - Common incident types and response proceduresFully autonomous decision engine with trial-and-error learning capabilities. Executes infrastructure operations without human intervention while leveraging reconciliation engines as safety nets. Learns from outcomes to improve future decisions through pattern recognition and adaptive optimization.
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