Developer Tools

Comprehensive Development Toolkit

ARKOS provides an extensive suite of developer tools designed to integrate seamlessly with existing workflows while introducing powerful new capabilities. These tools enhance productivity without disrupting established development practices, creating a unified experience across all development activities.

Command Line Interface

Powerful CLI Experience: The ARKOS CLI provides complete platform control through an intuitive, feature-rich command-line interface. Developers can deploy agents, configure workflows, monitor performance, and manage resources using familiar terminal commands with comprehensive help and autocomplete features.

Intelligent Command Completion: Advanced autocompletion understands context and provides relevant suggestions based on current project state, available agents, and historical usage patterns.

Scripting and Automation: Full scripting support enables automation of complex workflows, integration with CI/CD pipelines, and custom tooling development.

# ARKOS CLI Comprehensive Examples

# Project initialization with intelligent defaults
arkos init --project-type=webapp --stack=node --template=enterprise
arkos init --project-type=api --stack=python --database=postgresql

# Agent deployment and management
arkos agents deploy nexus sentinel weaver --environment=production
arkos agents configure nexus --optimization-level=aggressive --languages=python,javascript
arkos agents configure sentinel --coverage-threshold=90 --edge-case-detection=true
arkos agents scale oracle --min-replicas=2 --max-replicas=10

# Real-time monitoring and diagnostics
arkos status --detailed --format=json
arkos logs nexus --follow --since=1h --level=error
arkos metrics --agent=all --timeframe=24h --export=csv
arkos health-check --comprehensive --include-dependencies

# Workflow orchestration
arkos workflow create ci-pipeline \
  --agents=nexus,sentinel,weaver \
  --trigger=git-push \
  --environment=staging
arkos workflow run ci-pipeline --branch=feature/new-ui --wait
arkos workflow schedule ci-pipeline --cron="0 2 * * *" --timezone=UTC

# Configuration management
arkos config set global.timeout=30
arkos config set nexus.learning_rate=adaptive
arkos config export --file=arkos-config.yaml --include-secrets=false
arkos config validate --environment=production

# Secrets management
arkos secrets add database-url --value=$DATABASE_URL --environment=production
arkos secrets rotate api-keys --schedule=monthly
arkos secrets audit --show-access-history

# Integration management
arkos integrate github --repo=myorg/myrepo --webhook-events=push,pull_request
arkos integrate slack --channel=#development --notifications=all
arkos integrate aws --profile=production --region=us-east-1
arkos integrate monitoring --provider=datadog --api-key=$DATADOG_API_KEY

# Performance optimization
arkos optimize --target=cost --max-savings=30%
arkos optimize --target=performance --metric=response-time
arkos analyze infrastructure --recommendations=true

# Debugging and troubleshooting
arkos debug deployment --id=deploy-123 --verbose
arkos trace request --request-id=req-456 --full-stack
arkos diagnose performance --component=database --timeframe=1h

# Backup and disaster recovery
arkos backup create --include=configs,secrets,metrics
arkos restore --backup-id=backup-789 --environment=staging --confirm

# Advanced usage with piping and filtering
arkos metrics nexus --format=json | jq '.cpu_usage | max'
arkos logs --all-agents --since=1d | grep "ERROR" | arkos analyze patterns

REST API Framework

Comprehensive API Access: The ARKOS REST API provides complete access to all platform functionality through a well-designed, RESTful interface. The API features consistent response formats, comprehensive error handling, and extensive documentation with interactive examples.

Authentication and Security: Multiple authentication methods including API keys, OAuth 2.0, and JWT tokens. All API endpoints are secured with proper authentication and authorization checks.

Rate Limiting and Quotas: Intelligent rate limiting prevents abuse while allowing legitimate high-volume usage. Quotas align with subscription tiers and can be customized for enterprise needs.

Software Development Kits

Native SDK Support: Comprehensive SDKs for Python, JavaScript, Go, Java, and C# enable deep integration with existing applications. These SDKs handle authentication, request management, error handling, and response processing automatically.

# Python SDK - Comprehensive Integration Example
from arkos import ArkosClient, AgentConfig, WorkflowConfig
from arkos.exceptions import ArkosException
import asyncio
from typing import List, Dict, Any

class DevelopmentWorkflowManager:
    """
    Comprehensive ARKOS integration for development workflow automation.
    Demonstrates advanced SDK usage patterns and best practices.
    """
    
    def __init__(self, api_key: str, environment: str = "production"):
        self.client = ArkosClient(
            api_key=api_key,
            environment=environment,
            timeout=30,
            retry_attempts=3
        )
        self.environment = environment
        
    async def setup_project_automation(self, project_config: Dict[str, Any]) -> Dict[str, Any]:
        """
        Setup comprehensive automation for a development project.
        """
        try:
            # Analyze project characteristics
            project_analysis = await self.client.analyze_project(
                project_path=project_config['path'],
                technologies=project_config.get('technologies', []),
                team_size=project_config.get('team_size', 5)
            )
            
            # Configure agents based on analysis
            agent_configs = self._generate_agent_configurations(
                project_analysis, project_config
            )
            
            # Deploy agent cluster
            deployment_result = await self.client.agents.deploy_cluster(
                agents=agent_configs,
                environment=self.environment,
                auto_scale=True
            )
            
            # Setup automated workflows
            workflows = await self._create_automated_workflows(
                project_config, deployment_result
            )
            
            # Configure monitoring and alerts
            monitoring_config = await self._setup_monitoring(
                project_config, deployment_result, workflows
            )
            
            return {
                'project_analysis': project_analysis,
                'deployed_agents': deployment_result,
                'workflows': workflows,
                'monitoring': monitoring_config,
                'estimated_savings': project_analysis.get('estimated_savings', {})
            }
            
        except ArkosException as e:
            print(f"ARKOS API Error: {e.message}")
            raise
        except Exception as e:
            print(f"Unexpected error: {str(e)}")
            raise
    
    def _generate_agent_configurations(
        self, 
        analysis: Dict[str, Any], 
        project_config: Dict[str, Any]
    ) -> List[AgentConfig]:
        """Generate optimized agent configurations based on project analysis"""
        
        configs = []
        
        # Nexus configuration for code optimization
        nexus_config = AgentConfig(
            name="nexus",
            optimization_level="enterprise" if project_config.get('team_size', 0) > 10 else "standard",
            languages=analysis.get('detected_languages', []),
            architecture_patterns=analysis.get('architecture_patterns', []),
            learning_rate="adaptive",
            performance_monitoring=True
        )
        configs.append(nexus_config)
        
        # Sentinel configuration for comprehensive testing
        sentinel_config = AgentConfig(
            name="sentinel",
            coverage_threshold=project_config.get('coverage_target', 85),
            test_types=["unit", "integration", "e2e", "performance"],
            edge_case_detection=True,
            security_testing=project_config.get('security_required', True)
        )
        configs.append(sentinel_config)
        
        # Conditional agent deployment based on project needs
        if analysis.get('infrastructure_complexity', 'low') != 'low':
            oracle_config = AgentConfig(
                name="oracle",
                cloud_providers=project_config.get('cloud_providers', ['aws']),
                cost_optimization=True,
                predictive_scaling=True,
                disaster_recovery=project_config.get('dr_required', False)
            )
            configs.append(oracle_config)
        
        if project_config.get('security_requirements', 'standard') == 'high':
            aegis_config = AgentConfig(
                name="aegis",
                compliance_frameworks=project_config.get('compliance', []),
                threat_detection_sensitivity="high",
                auto_remediation=True
            )
            configs.append(aegis_config)
        
        return configs
    
    async def _create_automated_workflows(
        self, 
        project_config: Dict[str, Any], 
        deployment: Dict[str, Any]
    ) -> List[Dict[str, Any]]:
        """Create automated workflows for development processes"""
        
        workflows = []
        
        # Code review automation workflow
        code_review_workflow = WorkflowConfig(
            name="automated-code-review",
            trigger={
                "type": "pull_request",
                "branches": ["main", "develop"],
                "conditions": ["files_changed"]
            },
            steps=[
                {
                    "agent": "nexus",
                    "action": "analyze_code_changes",
                    "config": {"include_suggestions": True}
                },
                {
                    "agent": "sentinel", 
                    "action": "run_affected_tests",
                    "config": {"parallel": True}
                },
                {
                    "agent": "aegis",
                    "action": "security_scan",
                    "config": {"fail_on_high_severity": True}
                },
                {
                    "agent": "herald",
                    "action": "notify_reviewers",
                    "config": {"include_summary": True}
                }
            ],
            failure_handling="notify_and_block"
        )
        
        workflow_result = await self.client.workflows.create(code_review_workflow)
        workflows.append(workflow_result)
        
        # Deployment pipeline workflow
        deployment_workflow = WorkflowConfig(
            name="automated-deployment",
            trigger={
                "type": "merge_to_main",
                "conditions": ["tests_passed", "review_approved"]
            },
            steps=[
                {
                    "agent": "weaver",
                    "action": "prepare_deployment",
                    "config": {"environment": "staging"}
                },
                {
                    "agent": "sentinel",
                    "action": "run_integration_tests",
                    "config": {"environment": "staging"}
                },
                {
                    "agent": "oracle",
                    "action": "provision_resources",
                    "config": {"auto_scale": True}
                },
                {
                    "agent": "weaver",
                    "action": "deploy_application", 
                    "config": {"strategy": "blue_green"}
                },
                {
                    "agent": "aegis",
                    "action": "security_verification",
                    "config": {"environment": "production"}
                }
            ],
            rollback_on_failure=True
        )
        
        deployment_result = await self.client.workflows.create(deployment_workflow)
        workflows.append(deployment_result)
        
        return workflows
    
    async def monitor_project_health(self) -> Dict[str, Any]:
        """Monitor overall project health and performance"""
        
        # Get metrics from all agents
        agent_metrics = await self.client.metrics.get_agent_metrics(
            timeframe="24h",
            include_predictions=True
        )
        
        # Get workflow execution status
        workflow_status = await self.client.workflows.get_execution_status(
            timeframe="7d"
        )
        
        # Get cost analysis
        cost_analysis = await self.client.analytics.get_cost_analysis(
            include_projections=True,
            breakdown_by_agent=True
        )
        
        # Generate health score
        health_score = await self.client.analytics.calculate_health_score(
            metrics=agent_metrics,
            workflows=workflow_status,
            costs=cost_analysis
        )
        
        return {
            'health_score': health_score,
            'agent_performance': agent_metrics,
            'workflow_efficiency': workflow_status,
            'cost_optimization': cost_analysis,
            'recommendations': await self._generate_optimization_recommendations()
        }
    
    async def _generate_optimization_recommendations(self) -> List[Dict[str, Any]]:
        """Generate optimization recommendations based on current performance"""
        
        recommendations = await self.client.analytics.get_recommendations(
            categories=['performance', 'cost', 'security', 'productivity'],
            priority_threshold='medium'
        )
        
        return recommendations

# Usage example
async def main():
    workflow_manager = DevelopmentWorkflowManager(
        api_key="your_arkos_api_key",
        environment="production"
    )
    
    project_config = {
        'path': '/path/to/project',
        'technologies': ['python', 'react', 'postgresql'],
        'team_size': 12,
        'security_requirements': 'high',
        'compliance': ['soc2', 'gdpr'],
        'cloud_providers': ['aws', 'azure']
    }
    
    # Setup automation
    setup_result = await workflow_manager.setup_project_automation(project_config)
    print(f"Automation setup complete: {setup_result}")
    
    # Monitor health
    health_status = await workflow_manager.monitor_project_health()
    print(f"Project health score: {health_status['health_score']}")

if __name__ == "__main__":
    asyncio.run(main())

IDE Integration

Seamless Development Environment Integration: Deep integration with popular IDEs including VSCode, IntelliJ IDEA, and Vim. Real-time code assistance, optimization suggestions, and agent coordination appear directly within development environments.

Real-Time Collaboration: Agents provide real-time feedback and suggestions as code is written, enabling immediate optimization and quality improvements.

Custom Extensions: Extensible architecture allows development of custom IDE extensions that integrate with specific team workflows and requirements.

Webhook and Event System

Real-Time Event Processing: Comprehensive webhook system enables real-time integration with external tools and services. Events are processed immediately with reliable delivery and retry mechanisms.

Custom Event Handling: Flexible event handling supports custom business logic, complex routing rules, and integration with proprietary systems.

Event Analytics: Detailed analytics about event processing, delivery rates, and integration health provide insights into system performance and reliability.