// cognitive.fbs
// Schema definitions for cognitive architecture components
// Implements the seven-layer cognitive model
// Version: 1.0.0
include "base_types.fbs";
include "protocol.fbs";
namespace mcp.fbs.v1.cognitive;
// ============================================================================
// Layer 1: Perceptual Prompts - Understanding Context
// ============================================================================
// Context classification for project types
enum ProjectType: byte {
Unknown = 0,
WebService = 1,
CommandLineTool = 2,
Library = 3,
EmbeddedSystem = 4,
MobileApp = 5,
DesktopApp = 6,
DataPipeline = 7,
MachineLearning = 8
}
// Domain classification for specialized knowledge
enum Domain: byte {
General = 0,
SoftwareDevelopment = 1,
MedicalAnalysis = 2,
FinancialModeling = 3,
CreativeProduction = 4,
Infrastructure = 5,
DataScience = 6,
Security = 7
}
// Project context detected through perceptual analysis
table ProjectContext {
project_type: ProjectType;
primary_language: string;
languages: [string];
domain: Domain;
build_system: string;
has_tests: bool;
has_ci: bool;
performance_critical: bool;
safety_critical: bool;
security_sensitive: bool;
real_time_constraints: bool;
detected_frameworks: [string];
confidence: mcp.fbs.v1.Confidence;
detection_timestamp: mcp.fbs.v1.Timestamp;
metadata: [mcp.fbs.v1.KeyValue];
}
// Analysis goal classification
enum AnalysisGoal: byte {
BugFinding = 0,
PerformanceOptimization = 1,
SecurityAudit = 2,
CodeQuality = 3,
Diagnosis = 4,
Refactoring = 5,
Documentation = 6
}
// Risk profile assessment
enum RiskLevel: byte {
Low = 0,
Medium = 1,
High = 2,
Critical = 3
}
table RiskProfile {
overall_risk: RiskLevel;
failure_impact: string;
regulatory_requirements: [string];
data_sensitivity: RiskLevel;
availability_requirements: RiskLevel;
recommended_analysis_depth: string;
metadata: [mcp.fbs.v1.KeyValue];
}
// ============================================================================
// Layer 2: Episodic Memory - Specific Experiences
// ============================================================================
// Problem signature for identifying similar situations
table ProblemSignature {
symptoms: [string] (required);
context_fingerprint: string;
error_patterns: [string];
affected_components: [string];
reproduction_conditions: [string];
}
// Investigation step in diagnostic process
table InvestigationStep {
step_number: uint32;
action: string (required);
tool_used: string;
findings: string;
led_to_solution: bool;
duration_ms: uint32;
}
// Solution pattern that resolved an issue
table SolutionPattern {
description: string (required);
implementation_steps: [string];
validation_method: string;
side_effects: [string];
applicability_conditions: [string];
}
// Episodic memory entry capturing a specific experience
table EpisodeMemory {
id: mcp.fbs.v1.UUID (required);
name: string (required, key); // Using name as key instead of UUID
problem_signature: ProblemSignature (required);
context: ProjectContext (required);
investigation_path: [InvestigationStep];
solution: SolutionPattern (required);
success: bool;
cognitive_load: float; // Difficulty rating 0-10
generalization_cues: [string];
tags: [string];
created_at: mcp.fbs.v1.Timestamp;
used_count: uint32;
effectiveness_score: float;
related_episodes: [mcp.fbs.v1.UUID];
}
// ============================================================================
// Layer 3: Semantic Memory - Generalized Knowledge
// ============================================================================
// Conceptual understanding of domain principles
table ConceptualKnowledge {
concept_name: string (required, key);
definition: string (required);
principles: [string];
relationships: [mcp.fbs.v1.KeyValue]; // Related concepts
examples: [string];
anti_patterns: [string];
domain: Domain;
abstraction_level: uint8; // 0=concrete, 10=abstract
metadata: [mcp.fbs.v1.KeyValue];
}
// Domain model encoding structure and relationships
table DomainModel {
domain: Domain; // Enum cannot be required
components: [string];
interactions: [mcp.fbs.v1.KeyValue];
common_patterns: [string];
failure_modes: [string];
best_practices: [string];
constraints: [string];
version: mcp.fbs.v1.Version;
}
// Tool capability knowledge
table ToolCapabilityKnowledge {
tool_name: string (required, key);
purpose: string;
strengths: [string];
limitations: [string];
complementary_tools: [string];
best_use_cases: [string];
configuration_guidance: [mcp.fbs.v1.KeyValue];
performance_characteristics: [mcp.fbs.v1.KeyValue];
}
// ============================================================================
// Layer 4: Procedural Memory - Workflows and Techniques
// ============================================================================
// Decision point in a workflow
table DecisionPoint {
condition: string (required);
true_branch: string; // Reference to next step or workflow
false_branch: string;
evaluation_criteria: [string];
}
// Workflow step with optional branching
table WorkflowStep {
step_id: string (required);
description: string (required);
action: string (required);
tool: string;
parameters: [mcp.fbs.v1.KeyValue];
expected_output: string;
decision_point: DecisionPoint;
next_step: string;
alternatives: [string];
}
// Complete workflow template
table WorkflowTemplate {
id: mcp.fbs.v1.UUID (required);
name: string (required, key); // Using name as key instead of UUID
description: string;
goal: AnalysisGoal;
applicable_contexts: [ProjectType];
steps: [WorkflowStep] (required);
entry_point: string (required);
exit_conditions: [string];
estimated_duration_ms: uint32;
complexity_score: float;
success_rate: float;
usage_count: uint32;
version: mcp.fbs.v1.Version;
}
// Analytical technique description
table Technique {
name: string (required, key);
description: string (required);
method: string;
applicable_situations: [string];
examples: [string];
pitfalls: [string];
related_techniques: [string];
}
// Configuration recipe for tool usage
table ConfigurationRecipe {
tool_name: string (required);
context: ProjectContext;
configuration: [mcp.fbs.v1.KeyValue] (required);
rationale: [mcp.fbs.v1.KeyValue];
expected_behavior: string;
performance_impact: string;
success_rate: float;
}
// ============================================================================
// Layer 5: Meta-Cognitive - Self-Awareness and Strategy
// ============================================================================
// Strategy for approaching problems
enum Strategy: byte {
HypothesisDriven = 0,
SystematicEnumeration = 1,
BinarySearch = 2,
TopDown = 3,
BottomUp = 4,
Incremental = 5,
Experimental = 6
}
// Context factors influencing strategy selection
table ContextFactors {
time_pressure: RiskLevel;
information_availability: RiskLevel;
failure_impact: RiskLevel;
team_expertise: float;
resource_constraints: [string];
observability_quality: float;
}
// Strategy recommendation with reasoning
table StrategyRecommendation {
recommended_strategy: Strategy;
reasoning: string (required);
context_factors: ContextFactors (required);
alternative_strategies: [Strategy];
confidence: mcp.fbs.v1.Confidence;
}
// Self-assessment of understanding
table EpistemicState {
topic: string (required);
confidence_level: float; // 0.0 to 1.0
evidence_quality: RiskLevel;
knowledge_gaps: [string];
assumptions: [string];
certainty_source: string; // "direct evidence", "inference", "pattern matching"
last_validated: mcp.fbs.v1.Timestamp;
}
// Learning opportunity recognition
table LearningOpportunity {
situation_id: mcp.fbs.v1.UUID (required);
opportunity_type: string; // "novel pattern", "unexpected success", "contradiction"
significance_score: float;
capture_recommendation: string;
reasoning: string;
suggested_tags: [string];
}
// ============================================================================
// Layer 6: Cross-Domain Transfer - Analogical Reasoning
// ============================================================================
// Abstract pattern independent of domain
table AbstractPattern {
pattern_id: mcp.fbs.v1.UUID (required);
name: string (required, key); // Using name as key instead of UUID
abstract_structure: string (required);
relationships: [string];
constraints: [string];
applicability_conditions: [string];
source_domain: Domain;
instantiations: [mcp.fbs.v1.UUID]; // Concrete examples
effectiveness_across_domains: [mcp.fbs.v1.KeyValue];
}
// Structural mapping between domains
table StructuralMapping {
source_domain: Domain; // Enum cannot be required
target_domain: Domain; // Enum cannot be required
source_concepts: [string];
target_concepts: [string];
concept_mappings: [mcp.fbs.v1.KeyValue] (required);
relationship_mappings: [mcp.fbs.v1.KeyValue];
validity_conditions: [string];
examples: [string];
confidence: mcp.fbs.v1.Confidence;
}
// Transferable principle extracted from specific knowledge
table TransferablePrinciple {
principle_id: mcp.fbs.v1.UUID (required);
name: string (required, key); // Using name as key instead of UUID
abstract_description: string (required);
underlying_mechanism: string;
source_domains: [Domain];
applicable_domains: [Domain];
instantiation_examples: [mcp.fbs.v1.KeyValue];
validation_evidence: [string];
}
// ============================================================================
// Layer 7: Evaluative - Judgment and Quality Assessment
// ============================================================================
// Quality dimensions for assessment
table QualityMetrics {
thoroughness: float; // 0.0 to 1.0
accuracy: float;
actionability: float;
clarity: float;
efficiency: float;
completeness: float;
overall_score: float;
assessment_reasoning: string;
}
// Analysis quality assessment
table AnalysisQualityAssessment {
analysis_id: mcp.fbs.v1.UUID (required);
quality_metrics: QualityMetrics (required);
identifies_root_cause: bool;
provides_actionable_recommendations: bool;
evidence_strength: RiskLevel;
expert_review_rating: float;
improvement_suggestions: [string];
assessed_at: mcp.fbs.v1.Timestamp;
}
// Explanation effectiveness assessment
table ExplanationAssessment {
explanation_id: mcp.fbs.v1.UUID (required);
provides_insight: bool;
appropriate_technical_level: bool;
includes_context: bool;
explains_why_not_just_what: bool;
actionable_guidance: bool;
user_satisfaction_score: float;
improvement_notes: [string];
}
// Priority judgment for resource allocation
enum Priority: byte {
Defer = 0,
Low = 1,
Medium = 2,
High = 3,
Critical = 4
}
table PriorityJudgment {
item_id: mcp.fbs.v1.UUID (required);
priority: Priority;
criticality: RiskLevel;
effort_estimate: uint32; // minutes
expected_value: float;
reasoning: string (required);
dependencies: [mcp.fbs.v1.UUID];
}
// Aesthetic judgment about solutions
table AestheticJudgment {
solution_id: mcp.fbs.v1.UUID (required);
elegance_score: float;
simplicity_score: float;
robustness_score: float;
maintainability_score: float;
overall_quality: float;
reasoning: string;
exemplifies_principles: [string];
violates_principles: [string];
}
// ============================================================================
// Enhanced Prompt Definition for Cognitive System
// ============================================================================
enum PromptLayer: byte {
Unknown = 0,
Perceptual = 1,
Episodic = 2,
Semantic = 3,
Procedural = 4,
MetaCognitive = 5,
Transfer = 6,
Evaluative = 7
}
// Extended prompt with cognitive metadata
table CognitivePrompt {
base_prompt: mcp.fbs.v1.protocol.Prompt (required);
layer: PromptLayer;
domain: Domain;
tags: [string];
related_prompts: [mcp.fbs.v1.UUID];
parent_prompt: mcp.fbs.v1.UUID; // For derived prompts
derived_from_episodes: [mcp.fbs.v1.UUID];
abstraction_level: uint8;
applicability_score: [mcp.fbs.v1.KeyValue]; // Context -> score
statistics: mcp.fbs.v1.Statistics;
effectiveness_by_context: [mcp.fbs.v1.KeyValue];
last_updated: mcp.fbs.v1.Timestamp;
version_history: [mcp.fbs.v1.Version];
}
root_type CognitivePrompt;
