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Use when you need to coordinate and manage complex workflows across cloud environments. Orchestrates multi-step processes, handles dependencies, manages state, and provides workflow execution tracking for automation pipelines and business processes.
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SOC 職業分類に基づく
| name | manage-workflows |
| description | Use when you need to coordinate and manage complex workflows across cloud environments. Orchestrates multi-step processes, handles dependencies, manages state, and provides workflow execution tracking for automation pipelines and business processes. |
| 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 workflow management 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/workflow-management.py: Main automation implementationcore/scripts/automation/workflow-management_handler.py: Cloud-specific operationscore/scripts/automation/multi_cloud_orchestrator.py: Cross-provider coordinationworkflow, management, automation, enterprise, multi-cloud, aws, azure, gcp, onprem
Load these files when needed:
scripts/workflow-engine.py - Core workflow execution and state managementscripts/dependency-resolver.py - Workflow dependency analysis and resolutionreferences/workflow-patterns.md - Common workflow patterns and best practicesassets/workflow-templates.yaml - Reusable workflow templates for common processesexamples/workflow-examples/ - Complete workflow examples for different use casesFully 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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