ReasoningBank Intelligence

This is an adaptive learning system that lets AI agents learn from their own experience and optimize strategies over time. It's built on top of agentic-flow and gives agents meta-cognitive capabilities, so they can recognize patterns and continuously improve rather than starting fresh each time. You'd reach for this when you're building agents that need to get smarter through repeated interactions or long-running tasks. The implementation requires AgentDB for persistence, which makes sense since you're storing learned behaviors. It's part of the broader claude-flow toolkit from ruvnet, which has solid community traction. Fair warning: this is a more advanced pattern, not a drop-in solution for simple tasks.

GitHub stars: 67.2K
last updated: Aug 21, 2026

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Install

$ npx -y skills add ruvnet/ruflo --skill 'ReasoningBank Intelligence' --agent claude-code

Installs into .claude/skills of the current project.

Files

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

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'
});