Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination

Agentic Jujutsu AI Agent Version Control Quantum ready, self learning version control designed for multiple AI agents working simultaneously without conflicts. When to Use This Skill Use agentic jujutsu when you need: ✅ Multiple AI agents modifying code simultaneously ✅ Lock free version control (23x faster than Git) ✅ Self learning AI that improves from experience ✅ Quantum resistant security for future proof protection ✅ Automatic conflict resolution (87% success rate) ✅ Pattern recognition and intelligent suggestions ✅ Multi agent coordination without blocking Quick Start Installation Basic Usage Core Capabilities 1. Self Learning with ReasoningBank Track operations, learn patterns, and get intelligent suggestions: Validation (v2.3.1) : ✅ Tasks must be non empty (max 10KB) ✅ Success scores must be 0.0 1.0 ✅ Must have operations before finalizing ✅ Contexts cannot be empty 2. Pattern Discovery Automatically identify successful operation sequences: 3. Learning Statistics Track improvement over time: 4. Multi Agent Coordination Multiple agents work concurrently without conflicts: 5. Quantum Resistant Security (v2.3.0+) Fast integrity verification with quantum resistant cryptography: 6. Operation Tracking with AgentDB Automatic tracking of all operations: Advanced Use Cases Use Case 1: Adaptive Workflow Optimization Learn and improve deployment workflows: Use Case 2: Multi Agent Code Review Coordinate review across multiple agents: Use Case 3: Error Pattern Detection Learn from failures to prevent future issues: Use Case 4: Continuous Learning Loop Implement a self improving agent: API Reference Core Methods Method Description Returns new JjWrapper() Create wrapper instance JjWrapper status() Get repository status Promise<JjResult newCommit(msg) Create new commit Promise<JjResult log(limit) Show commit history Promise<JjCommit[] diff(from, to) Show differences Promise<JjDiff branchCreate(name, rev?) Create branch Promise<JjResult rebase(source, dest) Rebase commits Promise<JjResult ReasoningBank Methods Method Description Returns startTrajectory(task) Begin learning trajectory string (trajectory ID) addToTrajectory() Add recent operations void finalizeTrajectory(score, critique?) Complete trajectory (score: 0.0 1.0) void getSuggestion(task) Get AI recommendation JSON: DecisionSuggestion getLearningStats() Get learning metrics JSON: LearningStats getPatterns() Get discovered patterns JSON: Pattern[] queryTrajectories(task, limit) Find similar trajectories JSON: Trajectory[] resetLearning() Clear learned data void AgentDB Methods Method Description Returns getStats() Get operation statistics JSON: Stats getOperations(limit) Get recent operations JjOperation[] getUserOperations(limit) Get user operations only JjOperation[] clearLog() Clear operation log void Quantum Security Methods (v2.3.0+) Method Description Returns generateQuantumFingerprint(data) Generate SHA3 512 fingerprint Buffer (64 bytes) verifyQuantumFingerprint(data, fp) Verify fingerprint boolean enableEncryption(key, pubKey?) Enable HQC 128 encryption void disableEncryption() Disable encryption void isEncryptionEnabled() Check encryption status boolean Performance Characteristics Metric Git Agentic Jujutsu Concurrent commits 15 ops/s 350 ops/s (23x) Context switching 500 1000ms 50 100ms (10x) Conflict resolution 30 40% auto 87% auto (2.5x) Lock waiting 50 min/day 0 min (∞) Quantum fingerprints N/A <1ms Best Practices 1. Trajectory Management 2. Pattern Recognition 3. Multi Agent Coordination 4. Error Handling Validation Rules (v2.3.1+) Task Description ✅ Cannot be empty or whitespace only ✅ Maximum length: 10,000 bytes ✅ Automatically trimmed Success Score ✅ Must be finite (not NaN or Infinity) ✅ Must be between 0.0 and 1.0 (inclusive) Operations ✅ Must have at least one operation before finalizing Context ✅ Cannot be empty ✅ Keys cannot be empty or whitespace only ✅ Keys max 1,000 bytes, values max 10,000 bytes Troubleshooting Issue: Low Confidence Suggestions Issue: Validation Errors Issue: No Patterns Discovered Examples Example 1: Simple Learning Workflow Example 2: Multi Agent Swarm Related Documentation NPM Package : https://npmjs.com/package/agentic jujutsu GitHub : https://github.com/ruvnet/agentic flow/tree/main/packages/agentic jujutsu Full README : See package README.md Validation Guide : docs/VALIDATION FIXES v2.3.1.md AgentDB Guide : docs/AGENTDB GUIDE.md Version History v2.3.2 Documentation updates v2.3.1 Validation fixes for ReasoningBank v2.3.0 Quantum resistant security with @qudag/napi core v2.1.0 Self learning AI with ReasoningBank v2.0.0 Zero dependency installation with embedded jj binary Status : ✅ Production Ready License : MIT Maintained : Active

agentic-jujutsu