# Platform Integration Requirements Research ## Research Overview This document compiles comprehensive research on technical requirements and best practices for integrating the JAEGIS method with major AI platforms: Claude Code, Gemini Gems, and ChatGPT Custom GPTs. ## Claude Code Integration ### Platform Overview **Source**: Anthropic Claude Code Documentation * **Description**: Terminal-based AI coding assistant with built-in tools and agent capabilities * **Target Users**: Developers working in terminal environments * **Key Features**: Direct terminal integration, file system access, code generation and editing * **Architecture**: Local agent with cloud AI backend ### Technical Requirements ```yaml claude_code_integration: system_requirements: - Terminal access (bash, zsh, PowerShell) - Python 3.8+ environment - Network connectivity for API calls - File system read/write permissions api_requirements: - Anthropic API key and authentication - Claude API access (Claude-3.5-Sonnet or newer) - Rate limiting compliance (varies by plan) - Request/response format compatibility development_environment: - Local development setup - Version control integration (Git) - Package management (pip, npm, etc.) - IDE/editor integration capabilities ``` ### Integration Architecture ```yaml claude_code_architecture: integration_approach: "MCP_Server_Integration" mcp_server_setup: description: "Model Context Protocol server for JAEGIS integration" components: - "JAEGIS MCP Server" - "Agent orchestration endpoints" - "Template rendering services" - "Workflow execution handlers" communication_flow: - "Claude Code → MCP Server → JAEGIS Engine" - "JAEGIS Engine → MCP Server → Claude Code" - "Real-time bidirectional communication" data_exchange: format: "JSON-RPC 2.0" transport: "HTTP/WebSocket" authentication: "API key + session tokens" ``` ### Implementation Specifications ```yaml claude_code_implementation: jaegis_commands: - "jaegis init [project-type]" - "jaegis brainstorm [topic]" - "jaegis prd [project-name]" - "jaegis architecture [project-name]" - "jaegis develop [feature]" file_integration: - "Automatic file creation and editing" - "Template instantiation" - "Code generation and modification" - "Documentation updates" workflow_integration: - "Step-by-step guided workflows" - "Interactive agent conversations" - "Progress tracking and resumption" - "Quality validation checkpoints" ``` ## Gemini Gems Integration ### Platform Overview **Source**: Google AI Studio and Gemini API Documentation * **Description**: Custom AI assistants (Gems) with specialized capabilities * **Target Users**: Google ecosystem users and developers * **Key Features**: Custom instructions, conversation memory, Google services integration * **Architecture**: Cloud-based with Google AI Studio interface ### Technical Requirements ```yaml gemini_gems_integration: platform_requirements: - Google account with Gemini access - Google AI Studio access - Gemini API key (for programmatic access) - Google Cloud Platform account (for advanced features) api_specifications: - Gemini API v1 or newer - REST API with JSON payloads - OAuth 2.0 authentication - Rate limiting (varies by tier) development_tools: - Google AI Studio for Gem creation - Vertex AI for enterprise deployment - Google Cloud SDK for automation - Function calling capabilities ``` ### Gem Architecture Design ```yaml gemini_gems_architecture: gem_types: jaegis_orchestrator: description: "Main JAEGIS method coordinator" capabilities: - "Workflow orchestration" - "Agent selection and coordination" - "Progress tracking" - "Quality assurance" jaegis_brainstorming: description: "Specialized brainstorming facilitator" capabilities: - "Psychology-backed brainstorming" - "Creative ideation techniques" - "Collaborative idea development" jaegis_product_manager: description: "PRD creation specialist" capabilities: - "Requirements gathering" - "Stakeholder analysis" - "Feature prioritization" - "User story development" jaegis_architect: description: "Technical architecture specialist" capabilities: - "System design" - "Technology selection" - "Architecture documentation" - "Technical validation" ``` ### Implementation Strategy ```yaml gemini_gems_implementation: gem_creation_process: - "Define Gem personality and expertise" - "Configure system instructions" - "Set up conversation starters" - "Enable function calling for JAEGIS APIs" - "Test and validate Gem behavior" integration_methods: direct_api: - "Gemini API calls from JAEGIS system" - "Custom function definitions" - "Real-time conversation management" google_ai_studio: - "Manual Gem configuration" - "Template-based setup" - "User-driven interaction" vertex_ai: - "Enterprise deployment" - "Scalable infrastructure" - "Advanced monitoring and analytics" ``` ## ChatGPT Custom GPT Integration ### Platform Overview **Source**: OpenAI Platform Documentation and Custom GPT Guidelines * **Description**: Customized versions of ChatGPT with specific instructions and capabilities * **Target Users**: ChatGPT Plus/Pro subscribers and developers * **Key Features**: Custom instructions, actions (API calls), file uploads, web browsing * **Architecture**: Cloud-based with OpenAI infrastructure ### Technical Requirements ```yaml chatgpt_custom_gpt_integration: platform_requirements: - ChatGPT Plus or Pro subscription - OpenAI developer account (for actions) - Custom GPT creation access - API endpoints for actions api_specifications: - OpenAI API compatibility - RESTful API design - JSON schema definitions - OAuth 2.0 or API key authentication development_constraints: - No direct API access to Custom GPTs - Actions limited to external API calls - File upload size limitations - Rate limiting per user session ``` ### Custom GPT Architecture ```yaml custom_gpt_architecture: gpt_configuration: jaegis_orchestrator_gpt: name: "JAEGIS Method Orchestrator" description: "Master coordinator for JAEGIS methodology" instructions: "Comprehensive JAEGIS workflow guidance" actions: - "JAEGIS API for workflow management" - "Template generation services" - "Progress tracking endpoints" jaegis_brainstorming_gpt: name: "JAEGIS Brainstorming Specialist" description: "Psychology-backed brainstorming facilitator" instructions: "Advanced elicitation techniques" actions: - "Brainstorming session API" - "Idea evaluation services" - "Creative technique library" jaegis_pm_gpt: name: "JAEGIS Product Manager" description: "PRD creation and requirements specialist" instructions: "Product management expertise" actions: - "PRD template API" - "Requirements validation services" - "Stakeholder analysis tools" ``` ### Implementation Approach ```yaml custom_gpt_implementation: action_development: jaegis_api_server: description: "Backend API server for JAEGIS functionality" endpoints: - "POST /api/v1/brainstorm" - "POST /api/v1/prd/generate" - "POST /api/v1/architecture/design" - "GET /api/v1/templates/{type}" authentication: "API key based" rate_limiting: "Per-user quotas" data_validation: "JSON schema validation" gpt_configuration: system_instructions: - "JAEGIS methodology expertise" - "Collaborative interaction patterns" - "Quality assurance standards" - "User guidance and support" conversation_starters: - "Let's start a new JAEGIS project" - "Help me brainstorm ideas" - "Create a PRD for my project" - "Design the technical architecture" ``` ## Cross-Platform Integration Strategy ### Unified JAEGIS API ```yaml unified_api_design: core_endpoints: - "POST /jaegis/v1/session/start" - "POST /jaegis/v1/brainstorm" - "POST /jaegis/v1/prd/generate" - "POST /jaegis/v1/architecture/design" - "POST /jaegis/v1/workflow/execute" - "GET /jaegis/v1/templates" - "GET /jaegis/v1/session/{id}/status" platform_adapters: claude_code_adapter: - "MCP server implementation" - "Terminal command interface" - "File system integration" gemini_gems_adapter: - "Function calling integration" - "Google AI Studio configuration" - "Vertex AI deployment" custom_gpt_adapter: - "Actions API implementation" - "JSON schema definitions" - "Authentication handling" ``` ### Data Synchronization ```yaml data_synchronization: session_management: - "Cross-platform session continuity" - "Progress synchronization" - "Context preservation" - "User preference sync" document_management: - "Template synchronization" - "Version control integration" - "Export/import capabilities" - "Format compatibility" user_experience: - "Consistent interaction patterns" - "Platform-specific optimizations" - "Seamless transitions" - "Unified progress tracking" ``` ## Security and Compliance ### Authentication and Authorization ```yaml security_framework: authentication: - "Platform-specific auth (API keys, OAuth)" - "Session management and tokens" - "Multi-factor authentication support" - "Secure credential storage" authorization: - "Role-based access control" - "Feature-level permissions" - "Rate limiting and quotas" - "Audit logging" data_protection: - "Encryption in transit (TLS 1.3)" - "Encryption at rest" - "Data anonymization options" - "GDPR compliance measures" ``` ### Privacy Considerations ```yaml privacy_framework: data_handling: - "Minimal data collection" - "User consent management" - "Data retention policies" - "Right to deletion" platform_compliance: claude_code: - "Local processing preference" - "API call logging" - "File access permissions" gemini_gems: - "Google privacy policies" - "Data sharing controls" - "Conversation history management" custom_gpt: - "OpenAI data usage policies" - "Action data handling" - "User conversation privacy" ``` ## Performance and Scalability ### Performance Requirements ```yaml performance_standards: response_times: - "API calls: <2 seconds" - "Template generation: <5 seconds" - "Workflow execution: <30 seconds" - "Document creation: <60 seconds" throughput: - "Concurrent users: 1000+" - "API requests/minute: 10,000+" - "Session management: 5,000+ active" reliability: - "Uptime: 99.9%" - "Error rate: <0.1%" - "Recovery time: <5 minutes" ``` ### Scalability Architecture ```yaml scalability_design: infrastructure: - "Microservices architecture" - "Container orchestration (Kubernetes)" - "Auto-scaling capabilities" - "Load balancing" caching: - "Template caching" - "Session state caching" - "API response caching" - "CDN for static assets" monitoring: - "Real-time performance metrics" - "Error tracking and alerting" - "Usage analytics" - "Capacity planning" ``` This research provides the comprehensive foundation for implementing robust, secure, and scalable integrations with all three major AI platforms while maintaining the core JAEGIS methodology principles and user experience.