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Context Agent ​

Overview ​

The Context Agent maintains, analyzes, and leverages contextual information to enhance user experience and system intelligence within the Mantis platform. It serves as the memory and awareness layer that enables intelligent, context-aware interactions across all platform components.

Purpose ​

The Context Agent operates as the central nervous system for contextual awareness, managing information about user sessions, data states, conversation history, and system interactions. It provides the foundation for intelligent responses, personalized experiences, and seamless workflow continuity.

Key Features ​

Context Management ​

  • Session state tracking and preservation
  • Conversation history maintenance and analysis
  • Data context understanding and retention
  • User preferences and behavior patterns
  • Workspace state monitoring and synchronization

Intelligent Context Analysis ​

  • Pattern recognition in user interactions
  • Context relevance scoring and filtering
  • Temporal awareness and time-based context
  • Spatial context for data and visualization relationships
  • Semantic understanding of context relationships

Context-Aware Responses ​

  • Personalized interactions based on user history
  • Continuity maintenance across sessions
  • Relevant information retrieval and presentation
  • Contextual suggestions and recommendations
  • Adaptive responses to changing contexts

Context Types ​

Context Categories

Each context type provides different layers of intelligence for personalized experiences.

User Context ​

User profile, preferences, and behavior patterns that inform personalized interactions.

Data Context ​

Dataset characteristics, relationships, and analysis history for informed data handling.

Workflow Context ​

Current tasks, objectives, and progress for seamless workflow continuity.

Interface Context ​

Current view, navigation history, and tool selections for intuitive interface behavior.

Temporal Context ​

Session duration, time-based data, and scheduling for time-aware interactions.

Example Context Usage ​

"Remember my preference for scatter plots when analyzing correlations"
"Continue from where I left off in the data analysis workflow"
"Adapt the interface based on my current task and previous actions"
"Provide suggestions based on my analysis history and preferences"
"Maintain context across different data visualization sessions"