reasoningbank-intelligence

# ReasoningBank Intelligence ## What This Skill Does Implements ReasoningBank's adaptive learning system for AI agents to learn from experience, recognize patterns, and optimize strategies over time. Enables meta-cognitive capabilities and continuous improvement. ## Prerequisites - agentic-flow v1.5.11+ - AgentDB v1.0.4+ (for persistence) - Node.js 18+ ## Quick Start ```typescript import { ReasoningBank } from 'agentic-flow$reasoningbank'; // Initialize ReasoningBank const rb = new ReasoningBank({ persist: true, learningRate: 0.1, adapter: 'agentdb' // Use AgentDB for storage }); // Record task outcome await rb.recordExperience({ task: 'code_review', approach: 'static_analysis_first', outcome: { success: true, metrics: { bugs_found: 5, time_taken: 120, false_positives: 1 } }, context: { language: 'typescript', complexity: 'medium' } }); // Get optimal strategy const strategy = await rb.recommendStrategy('code_review', { language: 'typescript', complexity: 'high' }); ``` ## Core Features ### 1. Pattern Recognition ```typescript // Learn patterns from data await rb.learnPattern({ pattern: 'api_errors_increase_after_deploy', triggers: ['deployment', 'traffic_spike'], actions: ['rollback', 'scale_up'], confidence: 0.85 }); // Match patterns const matches = await rb.matchPatterns(currentSituation); ``` ### 2. Strategy Optimization ```typescript // Compare strategies const comparison = await rb.compareStrategies('bug_fixing', [ 'tdd_approach', 'debug_first', 'reproduce_then_fix' ]); // Get best strategy const best = comparison.strategies[0]; console.log(`Best: ${best.name} (score: ${best.score})`); ``` ### 3. Continuous Learning ```typescript // Enable auto-learning from all tasks await rb.enableAutoLearning({ threshold: 0.7, // Only learn from high-confidence outcomes updateFrequency: 100 // Update models every 100 experiences }); ``` ## Advanced Usage ### Meta-Learning ```typescript // Learn about learning await rb.metaLearn({ observation: 'parallel_execution_faster_for_independent_tasks', confidence: 0.95, applicability: { task_types: ['batch_processing', 'data_transformation'], conditions: ['tasks_independent', 'io_bound'] } }); ``` ### Transfer Learning ```typescript // Apply knowledge from one domain to another await rb.transferKnowledge({ from: 'code_review_javascript', to: 'code_review_typescript', similarity: 0.8 }); ``` ### Adaptive Agents ```typescript // Create self-improving agent class AdaptiveAgent { async execute(task: Task) { // Get optimal strategy const strategy = await rb.recommendStrategy(task.type, task.context); // Execute with strategy const result = await this.executeWithStrategy(task, strategy); // Learn from outcome await rb.recordExperience({ task: task.type, approach: strategy.name, outcome: result, context: task.context }); return result; } } ``` ## Integration with AgentDB ```typescript // Persist ReasoningBank data await rb.configure({ storage: { type: 'agentdb', options: { database: '.$reasoning-bank.db', enableVectorSearch: true } } }); // Query learned patterns const patterns = await rb.query({ category: 'optimization', minConfidence: 0.8, timeRange: { last: '30d' } }); ``` ## Performance Metrics ```typescript // Track learning effectiveness const metrics = await rb.getMetrics(); console.log(` Total Experiences: ${metrics.totalExperiences} Patterns Learned: ${metrics.patternsLearned} Strategy Success Rate: ${metrics.strategySuccessRate} Improvement Over Time: ${metrics.improvement} `); ``` ## Best Practices 1. **Record consistently**: Log all task outcomes, not just successes 2. **Provide context**: Rich context improves pattern matching 3. **Set thresholds**: Filter low-confidence learnings 4. **Review periodically**: Audit learned patterns for quality 5. **Use vector search**: Enable semantic pattern matching ## Troubleshooting ### Issue: Poor recommendations **Solution**: Ensure sufficient training data (100+ experiences per task type) ### Issue: Slow pattern matching **Solution**: Enable vector indexing in AgentDB ### Issue: Memory growing large **Solution**: Set TTL for old experiences or enable pruning ## Learn More - ReasoningBank Guide: agentic-flow$src$reasoningbank/README.md - AgentDB Integration: packages$agentdb$docs$reasoningbank.md - Pattern Learning: docs$reasoning$patterns.md