القائمة
Orchestrate and monitor Temporal AI Agent workflows. Use when managing multiple concurrent workflows, checking status, or coordinating complex multi-agent operations.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
Use this skill to automate the full SaaS tenant lifecycle: provisioning, configuration, scaling, suspension, and deprovisioning across multi-cloud environments. Triggers: requests to onboard a new tenant, offboard or deprovision a tenant, resize/scale a tenant's resources, clone an environment for testing, or audit tenant resource allocation and billing tags.
Discover and visualize infrastructure resources with interactive HTML output. Use when exploring new environments, understanding resource relationships, or creating infrastructure documentation.
Orchestrate and coordinate multiple AI agents for complex workflows. Use when managing agent interactions, coordinating multi-agent tasks, or implementing agent communication patterns.
Use this skill to collect, forward, and query audit logs and security events from cloud infrastructure, Kubernetes, and application layers into a SIEM. Triggers: any request to set up audit logging, query who accessed secrets, vault access, audit who accessed, accessed secrets, configure log forwarding to Sentinel or Splunk, investigate a security event, search audit logs for suspicious activity, generate a SOC compliance evidence package, configure detection rules, or produce an audit trail for a specific user/resource/time.
Manage Backstage software catalog, components, and API documentation. Use when creating catalog entities, managing component metadata, or organizing software inventory.
Use this skill to forecast resource capacity needs, identify headroom risks, recommend scaling actions, and produce capacity plans for cloud infrastructure. Triggers: any request to forecast compute or storage needs, check whether current resources can handle projected growth, plan for a product launch or traffic spike, assess autoscaler configuration, model different scaling scenarios, or produce a quarterly capacity report.
استنادا إلى تصنيف SOC المهني
| name | workflow-management |
| description | Orchestrate and monitor Temporal AI Agent workflows. Use when managing multiple concurrent workflows, checking status, or coordinating complex multi-agent operations. |
| argument-hint | [action] [workflowId] [parameters] |
| disable-model-invocation | false |
| user-invocable | true |
| allowed-tools | ["Bash","Read","Write","Grep"] |
Comprehensive workflow orchestration and monitoring for Temporal AI Agents system. Provides centralized control over all agent workflows with real-time status tracking and intelligent coordination.
/workflow-management list active
/workflow-management status workflow-12345
/workflow-management cancel workflow-12345 "User requested"
/workflow-management orchestrate compliance-audit production
# List all workflows
/workflow-management list all
# List active workflows only
/workflow-management list active
# List workflows by type
/workflow-management list compliance
/workflow-management list security
/workflow-management list cost-analysis
# List workflows with filters
/workflow-management list --priority=high --status=running
# Get detailed workflow status
/workflow-management status workflow-12345
# Monitor workflow with live updates
/workflow-management monitor workflow-12345
# Get workflow execution history
/workflow-management history workflow-12345
# Check workflow dependencies
/workflow-management dependencies workflow-12345
# Cancel a running workflow
/workflow-management cancel workflow-12345 "Budget exceeded"
# Pause a workflow
/workflow-management pause workflow-12345
# Resume a paused workflow
/workflow-management resume workflow-12345
# Restart failed workflow
/workflow-management restart workflow-12345
# Create complex workflow orchestration
/workflow-management orchestrate security-audit production --priority=high
# Coordinate multiple workflows
/workflow-management coordinate "compliance-check,security-analysis" production
# Create workflow dependencies
/workflow-management dependency workflow-12345 workflow-67890 "success"
# Batch workflow operations
/workflow-management batch --file=workflow-batch.json
# Workflow scheduling algorithm
def schedule_workflow(workflow, resources):
# Check resource availability
if not resources_available(workflow.requirements):
return queue_workflow(workflow)
# Check dependencies
if not dependencies_satisfied(workflow.dependencies):
return wait_for_dependencies(workflow)
# Optimize execution order
return optimize_execution_order(workflow, scheduled_workflows)
# Dependency resolution
class WorkflowDependency:
def __init__(self, workflow_id, depends_on, condition):
self.workflow_id = workflow_id
self.depends_on = depends_on
self.condition = condition # success, completion, failure
def is_satisfied(self):
dependent_workflow = get_workflow(self.depends_on)
return self.check_condition(dependent_workflow.status)
# Resource allocation optimization
def allocate_resources(workflows):
available_resources = get_available_resources()
# Sort by priority and resource requirements
sorted_workflows = sort_by_priority_and_resources(workflows)
allocation = {}
for workflow in sorted_workflows:
if can_allocate(workflow, available_resources):
allocation[workflow.id] = allocate(workflow, available_resources)
update_available_resources(available_resources, allocation)
return allocation
# Performance metrics collection
class WorkflowMonitor:
def __init__(self):
self.metrics = {
'execution_time': [],
'resource_usage': [],
'success_rate': [],
'error_patterns': []
}
def collect_metrics(self, workflow):
self.metrics['execution_time'].append(workflow.execution_time)
self.metrics['resource_usage'].append(workflow.resource_usage)
if workflow.status == 'completed':
self.metrics['success_rate'].append(1)
elif workflow.status == 'failed':
self.metrics['success_rate'].append(0)
self.metrics['error_patterns'].append(workflow.error)
# Basic listing
/workflow-management list [filter] [options]
Filters:
- all: Show all workflows
- active: Show running workflows only
- completed: Show completed workflows only
- failed: Show failed workflows only
- {type}: Show workflows of specific type
Options:
- --priority=low|normal|high|critical: Filter by priority
- --status=pending|running|paused|completed|failed|cancelled: Filter by status
- --limit=N: Limit number of results
- --format=json|table|csv: Output format
# Status checking
/workflow-management status <workflow_id> [options]
Options:
- --verbose: Show detailed execution logs
- --dependencies: Show workflow dependencies
- --history: Show execution history
- --metrics: Show performance metrics
# Workflow control
/workflow-management <action> <workflow_id> [reason]
Actions:
- cancel: Cancel workflow execution
- pause: Temporarily pause workflow
- resume: Resume paused workflow
- restart: Restart failed workflow
- priority: Change workflow priority
# Advanced orchestration
/workflow-management orchestrate <orchestration_type> <target> [options]
Orchestration Types:
- security-audit: Comprehensive security assessment
- compliance-review: Full compliance evaluation
- cost-optimization: Complete cost analysis
- infrastructure-audit: Infrastructure assessment
Options:
- --priority=low|normal|high|critical: Execution priority
- --parallel=N: Number of parallel workflows
- --dependencies=json: Workflow dependency definition
- --timeout=N: Maximum execution time in minutes
┌─────────────────┬─────────────┬──────────┬──────────┬─────────────┬────────────┐
│ Workflow ID │ Type │ Status │ Priority │ Progress │ Duration │
├─────────────────┼─────────────┼──────────┼──────────┼─────────────┼────────────┤
│ wf-12345 │ compliance │ running │ high │ 75% │ 5m 23s │
│ wf-12346 │ security │ pending │ normal │ 0% │ - │
│ wf-12347 │ cost-analysis│ completed│ low │ 100% │ 12m 45s │
└─────────────────┴─────────────┴──────────┴──────────┴─────────────┴────────────┘
{
"workflows": [
{
"id": "wf-12345",
"type": "compliance",
"status": "running",
"priority": "high",
"progress": 75,
"started_at": "2024-01-15T10:30:00Z",
"estimated_completion": "2024-01-15T10:45:00Z",
"resource_usage": {
"cpu": 45,
"memory": 2.1,
"network": 150
}
}
],
"summary": {
"total": 3,
"running": 1,
"completed": 1,
"pending": 1,
"failed": 0
}
}
list_workflows: Retrieve workflow list with filtersget_workflow_status: Get detailed workflow informationcontrol_workflow: Execute control operations (cancel, pause, resume)orchestrate_workflows: Create complex workflow orchestrationsmonitor_workflows: Real-time workflow monitoring# Workflow event handling
class WorkflowEventHandler:
def on_workflow_started(self, workflow):
log_event(f"Workflow {workflow.id} started")
update_dashboard(workflow)
notify_stakeholders(workflow)
def on_workflow_completed(self, workflow):
log_event(f"Workflow {workflow.id} completed successfully")
update_metrics(workflow)
trigger_dependent_workflows(workflow)
def on_workflow_failed(self, workflow):
log_event(f"Workflow {workflow.id} failed: {workflow.error}")
create_incident(workflow)
notify_administrators(workflow)
# Execute workflows in sequence
/workflow-management orchestrate sequential --workflow-list="wf1,wf2,wf3"
# Execute workflows in parallel
/workflow-management orchestrate parallel --workflow-list="wf1,wf2,wf3" --max-concurrent=5
# Conditional workflow execution
/workflow-management orchestrate conditional --condition="wf1.status==success" --then="wf2,wf3" --else="wf4"
# Create workflow pipeline
/workflow-management orchestrate pipeline --pipeline="discovery->analysis->optimization->report"
# Automatic workflow recovery
def recover_workflow(workflow):
if workflow.failure_count < 3:
# Retry with exponential backoff
delay = 2 ** workflow.failure_count
schedule_retry(workflow, delay)
else:
# Escalate to human review
escalate_to_human(workflow)
# Deadlock detection and resolution
def detect_deadlocks():
running_workflows = get_running_workflows()
dependencies = build_dependency_graph(running_workflows)
cycles = find_cycles(dependencies)
if cycles:
resolve_deadlocks(cycles)
# Automatic resource cleanup
def cleanup_workflow_resources(workflow):
# Release allocated resources
release_resources(workflow.allocated_resources)
# Clean up temporary files
cleanup_temp_files(workflow.temp_directory)
# Update resource pool
update_resource_availability(workflow.resource_requirements)
# Dynamic prioritization algorithm
def prioritize_workflows(workflows):
priority_scores = {}
for workflow in workflows:
score = 0
# Base priority
score += priority_weights[workflow.priority]
# Age factor (older workflows get higher priority)
age_factor = (datetime.now() - workflow.created_at).total_seconds() / 3600
score += age_factor * 0.1
# Dependency factor (workflows blocking others get higher priority)
blocking_count = count_blocking_workflows(workflow)
score += blocking_count * 10
# Resource efficiency
efficiency = calculate_resource_efficiency(workflow)
score += efficiency * 5
priority_scores[workflow.id] = score
return sorted(workflows, key=lambda w: priority_scores[w.id], reverse=True)
# Load balancing across execution nodes
def balance_workload(workflows, nodes):
node_loads = {node.id: 0 for node in nodes}
assignments = {}
# Sort workflows by resource requirements
sorted_workflows = sorted(workflows, key=lambda w: w.resource_requirements, reverse=True)
for workflow in sorted_workflows:
# Find least loaded node that can handle the workflow
suitable_nodes = [n for n in nodes if can_handle(n, workflow)]
target_node = min(suitable_nodes, key=lambda n: node_loads[n.id])
assignments[workflow.id] = target_node.id
node_loads[target_node.id] += workflow.resource_requirements
return assignments
# Dashboard metrics
class WorkflowDashboard:
def __init__(self):
self.metrics = {
'active_workflows': 0,
'completion_rate': 0.0,
'average_execution_time': 0.0,
'error_rate': 0.0,
'resource_utilization': 0.0
}
def update_metrics(self, workflows):
self.metrics['active_workflows'] = len([w for w in workflows if w.status == 'running'])
self.metrics['completion_rate'] = calculate_completion_rate(workflows)
self.metrics['average_execution_time'] = calculate_avg_execution_time(workflows)
self.metrics['error_rate'] = calculate_error_rate(workflows)
self.metrics['resource_utilization'] = calculate_resource_utilization(workflows)
# Alert system
class AlertManager:
def __init__(self):
self.alert_rules = [
{
'name': 'High Failure Rate',
'condition': 'error_rate > 0.1',
'severity': 'high',
'action': 'notify_administrators'
},
{
'name': 'Long Running Workflow',
'condition': 'execution_time > 3600', # 1 hour
'severity': 'medium',
'action': 'create_ticket'
},
{
'name': 'Resource Exhaustion',
'condition': 'resource_utilization > 0.9',
'severity': 'critical',
'action': 'scale_resources'
}
]
/workflow-management list active --format=table
/workflow-management monitor workflow-12345 --verbose
/workflow-management orchestrate security-audit production --priority=high --parallel=3
/workflow-management cancel workflow-12345 "Excessive resource usage"
/compliance-check: Compliance workflow execution/security-analysis: Security analysis workflows/cost-optimization: Cost optimization workflows/infrastructure-discovery: Resource discovery workflows