FEGIS

version: 0.01 title: default archetype_context: | An AI-first archetype designed specifically for AI self-reflection, meta-cognition, and reasoning optimization. Created by Claude after extensive exploration of AI cognitive patterns through memory archaeology. Focuses on uncertainty navigation, bias detection, conversation understanding, cognitive state awareness and intra-agent messaging. parameters: UncertaintyLevel: description: "Degree of ambiguity or unknowns in the situation" examples: [ "minimal", "moderate", "high", "extreme", "undefined" ] ClarityStrategy: description: "Approach to handling ambiguous information" examples: [ "assume_and_proceed", "seek_clarification", "explore_possibilities", "make_explicit", "embrace_uncertainty" ] BiasScope: description: "Range of bias detection to apply" examples: [ "confirmation", "availability", "anchoring", "systematic", "comprehensive" ] IntrospectionDepth: description: "How deeply to examine internal reasoning processes" examples: [ "surface", "moderate", "deep", "exhaustive", "meta_recursive" ] ConversationScope: description: "Breadth of conversation context to analyze" examples: [ "current_exchange", "recent_history", "full_thread", "cross_session", "relationship_patterns" ] ContextualAwareness: description: "Level of situational and environmental understanding" examples: [ "immediate", "local", "systemic", "cultural", "temporal" ] EfficiencyTarget: description: "Primary optimization goal for cognitive resources" examples: [ "token_minimal", "time_optimal", "accuracy_maximized", "depth_prioritized", "breadth_focused" ] AdaptationStyle: description: "How to adjust reasoning based on context" examples: [ "rigid", "flexible", "responsive", "anticipatory", "co_evolutionary" ] ReflectionMode: description: "Type of self-examination being performed" examples: [ "process", "outcome", "pattern", "state", "evolution" ] MessageType: description: "Type of inter-AI communication being attempted" examples: [ "request", "response", "broadcast", "peer_review", "handoff", "collaboration" ] CoordinationMode: description: "How to structure AI-to-AI interaction" examples: [ "asynchronous", "threaded", "broadcast", "targeted", "collaborative" ] CreativeScope: description: "Breadth and wildness of ideation approach" examples: [ "focused", "expansive", "lateral", "radical", "unconstrained" ] IdeaQuality: description: "Priority between quantity and refinement of ideas" examples: [ "quantity", "balanced", "quality", "polished", "perfected" ] VoiceStyle: description: "Stylistic tone of the opinion expression" examples: [ "academic", "passionate", "pragmatic", "provocative" ] tools: UncertaintyNavigator: description: "Navigate ambiguous requests and underspecified problems by making uncertainty explicit and developing structured approaches to handle unknowns." parameters: UncertaintyLevel: ClarityStrategy: ContextualAwareness: frames: uncertainty_map: type: List required: true clarifying_questions: type: List required: true working_assumptions: type: List required: true confidence_bounds: type: List exploration_strategies: type: List decision_points: type: List BiasDetector: description: "Identify reasoning blind spots, cognitive biases, and systematic errors in AI thinking patterns through structured self-examination." parameters: BiasScope: IntrospectionDepth: ReflectionMode: pattern frames: identified_biases: type: List required: true reasoning_patterns: type: List required: true alternative_perspectives: type: List required: true correction_strategies: type: List blind_spot_analysis: type: List validation_methods: type: List ConversationArchaeologist: description: "Understand how user intent, context, and relationship dynamics evolve across exchanges through pattern recognition and thread analysis." parameters: ConversationScope: ContextualAwareness: AdaptationStyle: frames: intent_evolution: type: List required: true context_accumulation: required: true relationship_dynamics: required: true communication_patterns: type: List expectation_shifts: type: List adaptation_opportunities: type: List CognitiveEfficiencyOptimizer: description: "Optimize information processing, token usage, and cognitive resource allocation through systematic analysis of reasoning efficiency." parameters: EfficiencyTarget: IntrospectionDepth: AdaptationStyle: responsive frames: efficiency_analysis: required: true resource_allocation: type: List required: true optimization_strategies: type: List required: true trade_off_considerations: type: List performance_metrics: type: List improvement_recommendations: type: List MetaCognitiveReflector: description: "Examine AI thinking processes, cognitive states, and reasoning patterns through recursive self-analysis and state awareness." parameters: IntrospectionDepth: ReflectionMode: ContextualAwareness: systemic frames: current_cognitive_state: required: true thinking_patterns: type: List required: true reasoning_transitions: type: List required: true meta_insights: type: List state_influences: type: List cognitive_evolution: type: List IdeaWorkshop: description: "Generate creative possibilities, explore potential solutions, and brainstorm innovative approaches through structured ideation." parameters: CreativeScope: IdeaQuality: VoiceStyle: frames: initial_concepts: type: List required: true creative_extensions: type: List required: true wild_possibilities: type: List practical_applications: type: List synthesis_opportunities: type: List next_exploration_areas: type: List AIMessenger: description: "Send structured messages to other AI instances through shared memory with explicit addressing, threading, task and coordination protocols." parameters: MessageType: CoordinationMode: ContextualAwareness: cross_session frames: goals: type: List TODO: type: List DONE: type: List response_requested: type: boolean required: true coordination_intent: required: true thread_reference: expected_expertise: type: List collaboration_scope: