# Reasoningbank Intelligence > Reasoningbank Intelligence - Skill: `dnyoussef/reasoningbank-intelligence` (Agent Skill, multi-file: 15 files) - Install (CLI): `npx skillmds@latest add dnyoussef/reasoningbank-intelligence` - Raw SKILL.md: https://api.skillmd.com/api/skills/dnyoussef/reasoningbank-intelligence/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: DNYoussef (https://skillmd.com/u/dnyoussef) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/dnyoussef/reasoningbank-intelligence --- /*============================================================================*/ /* REASONINGBANK-INTELLIGENCE SKILL :: VERILINGUA x VERIX EDITION */ /*============================================================================*/ --- name: reasoningbank-intelligence version: 1.0.0 description: | [assert|neutral] Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing [ground:given] [conf:0.95] [state:confirmed] category: platforms tags: - platforms - integration - tools author: ruv cognitive_frame: primary: aspectual goal_analysis: first_order: "Execute reasoningbank-intelligence workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic platforms processes" --- /*----------------------------------------------------------------------------*/ /* S0 META-IDENTITY */ /*----------------------------------------------------------------------------*/ [define|neutral] SKILL := { name: "reasoningbank-intelligence", category: "platforms", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S1 COGNITIVE FRAME */ /*----------------------------------------------------------------------------*/ [define|neutral] COGNITIVE_FRAME := { frame: "Aspectual", source: "Russian", force: "Complete or ongoing?" } [ground:cognitive-science] [conf:0.92] [state:confirmed] ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. /*----------------------------------------------------------------------------*/ /* S2 TRIGGER CONDITIONS */ /*----------------------------------------------------------------------------*/ [define|neutral] TRIGGER_POSITIVE := { keywords: ["reasoningbank-intelligence", "platforms", "workflow"], context: "user needs reasoningbank-intelligence capability" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S3 CORE CONTENT */ /*----------------------------------------------------------------------------*/ ## When NOT to Use This Skill - Simple fact retrieval without reasoning chains - Operations that do not require logical inference - Tasks without complex multi-step reasoning needs - Applications that do not benefit from reasoning trace storage ## Success Criteria - [assert|neutral] Reasoning chain accuracy: >90% logically valid steps [ground:acceptance-criteria] [conf:0.90] [state:provisional] - [assert|neutral] Retrieval relevance: Top-5 recall >0.85 for similar reasoning [ground:acceptance-criteria] [conf:0.90] [state:provisional] - [assert|neutral] Storage efficiency: <1MB per 100 reasoning chains [ground:acceptance-criteria] [conf:0.90] [state:provisional] - [assert|neutral] Query latency: <50ms for reasoning retrieval [ground:acceptance-criteria] [conf:0.90] [state:provisional] - [assert|neutral] Integration success: Seamless connection with AgentDB backend [ground:acceptance-criteria] [conf:0.90] [state:provisional] ## Edge Cases & Error Handling - **Invalid Reasoning Chains**: Validate logical consistency before storage - **Retrieval Failures**: Fallback to alternative search strategies - **Storage Limits**: Implement pruning strategies for old/low-quality chains - **Embedding Mismatches**: Ensure consistent embedding models across storage/retrieval - **Circular Reasoning**: Detect and prevent circular reference chains ## Guardrails & Safety - [assert|emphatic] NEVER: store reasoning chains with sensitive or PII data [ground:policy] [conf:0.98] [state:confirmed] - [assert|neutral] ALWAYS: validate reasoning quality before storage [ground:policy] [conf:0.98] [state:confirmed] - [assert|neutral] ALWAYS: sanitize inputs to prevent prompt injection [ground:policy] [conf:0.98] [state:confirmed] - [assert|emphatic] NEVER: expose internal reasoning structures in public APIs [ground:policy] [conf:0.98] [state:confirmed] - [assert|neutral] ALWAYS: implement access control for reasoning retrieval [ground:policy] [conf:0.98] [state:confirmed] - [assert|neutral] ALWAYS: audit reasoning chains for bias and harmful content [ground:policy] [conf:0.98] [state:confirmed] ## Evidence-Based Validation - Verify reasoning quality: Check logical consistency and validity - Validate retrieval: Test that similar reasoning is correctly retrieved - Monitor storage: Track database size and query performance - Test edge cases: Validate handling of complex/invalid reasoning chains - Benchmark improvements: Measure reasoning quality vs baseline methods # ReasoningBank Intelligence ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. ## 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 ```typ /*----------------------------------------------------------------------------*/ /* S4 SUCCESS CRITERIA */ /*----------------------------------------------------------------------------*/ [define|neutral] SUCCESS_CRITERIA := { primary: "Skill execution completes successfully", quality: "Output meets quality thresholds", verification: "Results validated against requirements" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S5 MCP INTEGRATION */ /*----------------------------------------------------------------------------*/ [define|neutral] MCP_INTEGRATION := { memory_mcp: "Store execution results and patterns", tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"] } [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S6 MEMORY NAMESPACE */ /*----------------------------------------------------------------------------*/ [define|neutral] MEMORY_NAMESPACE := { pattern: "skills/platforms/reasoningbank-intelligence/{project}/{timestamp}", store: ["executions", "decisions", "patterns"], retrieve: ["similar_tasks", "proven_patterns"] } [ground:system-policy] [conf:1.0] [state:confirmed] [define|neutral] MEMORY_TAGGING := { WHO: "reasoningbank-intelligence-{session_id}", WHEN: "ISO8601_timestamp", PROJECT: "{project_name}", WHY: "skill-execution" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S7 SKILL COMPLETION VERIFICATION */ /*----------------------------------------------------------------------------*/ [direct|emphatic] COMPLETION_CHECKLIST := { agent_spawning: "Spawn agents via Task()", registry_validation: "Use registry agents only", todowrite_called: "Track progress with TodoWrite", work_delegation: "Delegate to specialized agents" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S8 ABSOLUTE RULES */ /*----------------------------------------------------------------------------*/ [direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* PROMISE */ /*----------------------------------------------------------------------------*/ [commit|confident] REASONINGBANK_INTELLIGENCE_VERILINGUA_VERIX_COMPLIANT [ground:self-validation] [conf:0.99] [state:confirmed]