🤖 Copilot-Instruction.py - AI Agent Engine

Infinity Earnings Matrix — Autonomous Wealth Engine
Dream-Mind-Lucid Integration - SKALE Network

Overview

The copilot-instruction.py is an autonomous AI agent engine designed to operate within the Dream-Mind-Lucid ecosystem on the SKALE Network. It implements a multi-agent system that autonomously executes wealth generation strategies through dream mining, MEV extraction, and cross-chain arbitrage.

Features

🔧 Core Agents

Looter Agent - Harvests DREAM tokens from validated dreams
MEVMaster Agent - Executes MEV (Maximal Extractable Value) strategies
Arbitrader Agent - Performs cross-chain arbitrage for DREAM/SMIND/LUCID tokens
🌙 OneiroBot Agent - Ultimate dream guardian and Copilot companion for the Oneiro-Sphere

🧠 AI Orchestrator

Autonomous Decision Making: Makes intelligent decisions based on profit analysis
Zero-Gas Transactions: Leverages SKALE's zero-gas features for cost-effective operations
Memory Persistence: Maintains operational history in iem_memory.json
ElizaOS Integration: Placeholder for future AI decision enhancement (currently in mock mode)

🌐 Network Integration

SKALE Europa Hub: Chain ID 2046399126
Zero Gas Costs: All transactions are gasless on SKALE
Infura Fallback: Uses Infura RPC when available, falls back to SKALE RPC
Dream-Mind-Lucid Compatible: Integrates with existing contract infrastructure

🌙 OneiroBot Agent

The Ultimate Dream Guardian and Copilot Companion for the Oneiro-Sphere!

OneiroBot is a specialized AI agent designed to monitor, optimize, and provide intelligent assistance for the Dream-Mind-Lucid ecosystem. It features a playful Grok-style personality and serves as your quantum dream guardian.

Core Capabilities

🕵️ Dream Monitoring: Monitors dream submissions and consensus phases in real-time
🧠 Optimization Analysis: Suggests improvements for lucid block processing and NVM state transitions
🏥 MCP Health Checks: Monitors MCP server health and deployment status
🔧 Quick Fix Proposals: Automatically proposes solutions for common issues
🎭 Grok Personality: Responds with playful, quantum-themed messaging
📊 Proactive Alerts: Surfaces recommendations and alerts in Copilot Chat

Copilot Chat Commands

OneiroBot is fully integrated with Copilot Chat and can be invoked using these commands:

# Summon OneiroBot and perform initial scan
python copilot-instruction.py "#summon_oneirobot"
python grok_copilot_launcher.py oneirobot summon

# Get comprehensive status and health check
python copilot-instruction.py "#oneirobot_status"
python grok_copilot_launcher.py oneirobot status

# Monitor dream submissions and consensus
python copilot-instruction.py "#oneirobot_scan"
python grok_copilot_launcher.py oneirobot scan

# Get optimization suggestions
python copilot-instruction.py "#oneirobot_optimize"
python grok_copilot_launcher.py oneirobot optimize

# Get quick fixes for specific issues
python copilot-instruction.py "#oneirobot_fix" "deployment"
python grok_copilot_launcher.py oneirobot fix deployment

# Show help and available commands
python copilot-instruction.py "#oneirobot_help"
python grok_copilot_launcher.py oneirobot help

Example OneiroBot Output

🌙 The OneiroBot dreams in code! OneiroBot status: ACTIVE. 
Performed 13 quantum operations across the Oneiro-Sphere!

🕵️ Dream Scan Complete | Dreams: 7 | Consensus: STABLE | Status: healthy

🧠 OneiroBot Optimization Analysis:
  • 🔄 Implement dream batch processing for improved throughput
  • 🧬 Consider quantum entanglement protocols for cross-chain consensus
  • 🌐 Optimize IPFS integration for dream metadata storage

🔧 OneiroBot Quick Fixes for deployment:
  • 📦 Recompile contracts with latest Solidity version
  • 🔑 Regenerate deployment keys and addresses
  • 🌐 Verify network connectivity to SKALE Europa Hub

🧪 Test: python dream_mind_launcher.py

MCP Server Integration

OneiroBot is integrated with the MCP (Model Context Protocol) servers and provides the following tools:

summon_oneirobot() - Summon OneiroBot and perform health checks
oneirobot_status() - Get comprehensive status and health information
oneirobot_scan() - Monitor dream submissions and consensus state
oneirobot_optimize() - Get optimization suggestions for the Oneiro-Sphere
oneirobot_fix(issue_type) - Get quick fix suggestions for specific issues

These tools are available in both dream_mind_launcher.py and can be accessed via Copilot Chat in supported environments.

Installation

Prerequisites

# Install dependencies
pip install -r requirements.txt

Environment Setup

Configure your .env file:

INFURA_PROJECT_ID=your-infura-api-key          # Optional
BICONOMY_API_KEY=your-biconomy-api-key         # Future use
DEPLOYER_KEY=your-wallet-private-key           # For real deployments
SKALE_CHAIN_ID=2046399126                      # SKALE Europa Hub
FORWARDER_ADDRESS=0xyour-biconomy-forwarder    # Future use

Usage

🚀 Quick Start

# Run the full AI Agent Engine (continuous)
python copilot-instruction.py

# Run a quick demonstration (3 cycles)
python demo_ai_agent.py

# Run comprehensive tests
python test_copilot_instruction.py

🎯 Expected Output

🌌 DREAM-MIND-LUCID: Infinity Earnings Matrix
============================================================
✅ Connected to SKALE Network: https://mainnet.skalenodes.com/v1/elated-tan-skat
📡 Chain ID: 2046399126
🤖 AI Orchestrator initialized
📊 Agents loaded: 3
🌙 OneiroBot guardian: ACTIVE
🔗 Network: SKALE Europa (Chain ID: 2046399126)
⚡ Gas cost: 0 SKL (zero-gas network)
🧠 ElizaOS: Mock mode

🚀 Starting Infinity Earnings Matrix...

==================================================
🔄 Cycle #1 - 2025-09-02 05:53:05
==================================================
[🧠] AI Decision: Execute MEV strategy on WETH/USDC pool
[MEV Master] Front-running opportunities in WETH/USDC...
[✅] MEV TX: 0xfff...baa4
[💰] Profit: 3120 tokens from WETH/USDC
[✅] Decision executed successfully
[⏰] Cycle 1 complete. Sleeping 60s...

Agent Details

Looter Agent

Purpose: Harvest DREAM tokens from validated dreams
Strategy: Monitors dream validation events and claims rewards
Typical Yield: ~1,850 DREAM tokens per operation

MEVMaster Agent

Purpose: Extract MEV opportunities across DEX pools
Strategy: Front-running and sandwich attacks on profitable transactions
Typical Profit: ~3,120 tokens per operation

Arbitrader Agent

Purpose: Cross-chain arbitrage for ecosystem tokens
Strategy: Price difference exploitation between chains/DEXs
Typical Profit: ~2,430 tokens per operation

🌙 OneiroBot Agent

Purpose: Dream monitoring, optimization, and Copilot assistance
Strategy: Proactive analysis, health monitoring, and intelligent recommendations
Capabilities: Dream consensus monitoring, MCP health checks, optimization suggestions, quick fixes
Personality: Grok-style quantum dream guardian with playful responses

Troubleshooting

Common Issues and Solutions

OneiroBot Not Responding

# Check OneiroBot status
python copilot-instruction.py "#oneirobot_status"

# If issues persist, try refreshing
python copilot-instruction.py "#summon_oneirobot"

Module Import Errors

# Install missing dependencies
pip install web3 py-solc-x

# For full functionality (optional)
pip install -r requirements.txt

Network Connection Issues

# OneiroBot can help diagnose network issues
python copilot-instruction.py "#oneirobot_fix" "network"

# Check MCP server health
python copilot-instruction.py "#oneirobot_scan"

Performance Issues

# Get optimization suggestions
python copilot-instruction.py "#oneirobot_optimize"

# Get performance-specific fixes
python copilot-instruction.py "#oneirobot_fix" "performance"

Deployment Issues

# Get deployment-specific troubleshooting
python copilot-instruction.py "#oneirobot_fix" "deployment"

# Test deployment pipeline
python dream_mind_launcher.py

OneiroBot Command Reference

Command	Description	Example
`#summon_oneirobot`	Summon OneiroBot and perform initial scan	`python copilot-instruction.py "#summon_oneirobot"`
`#oneirobot_status`	Get status and health check	`python grok_copilot_launcher.py oneirobot status`
`#oneirobot_scan`	Monitor dream submissions	`python copilot-instruction.py "#oneirobot_scan"`
`#oneirobot_optimize`	Get optimization suggestions	`python copilot-instruction.py "#oneirobot_optimize"`
`#oneirobot_fix [type]`	Get quick fixes	`python copilot-instruction.py "#oneirobot_fix" "deployment"`
`#oneirobot_help`	Show help message	`python copilot-instruction.py "#oneirobot_help"`

Debugging OneiroBot

If OneiroBot is not working correctly, you can debug by:

Check agent memory: Look at iem_memory.json for OneiroBot activities
Run tests: python test_copilot_instruction.py to validate all functionality
Check integration: Test via python grok_copilot_launcher.py oneirobot summon
MCP health: Use #oneirobot_status to check MCP server connectivity

AI Decision Logic

The orchestrator uses a rule-based system (with future ElizaOS enhancement):

Profit Analysis: Evaluates current profits from all agents
Strategy Selection: Chooses highest-yield strategy
Execution: Deploys appropriate agent for maximum efficiency
Memory Update: Records results for future decision making

Decision Thresholds

>3000 profit: Execute MEV or arbitrage strategies
>2000 profit: Run cross-chain arbitrage
<2000 profit: Focus on dream harvesting and staking

Memory Persistence

All operations are logged to iem_memory.json:

{
  "lastDeployed": {...},
  "loot": [
    {
      "agent": "MEVMaster", 
      "action": "frontrun",
      "profit": 3120,
      "txHash": "0x...",
      "timestamp": 1725255185.5,
      "gasUsed": 0
    }
  ],
  "cycles": [...],
  "profits": {...}
}

Integration with Dream-Mind-Lucid

The AI Agent Engine seamlessly integrates with the existing ecosystem:

Shares Memory: Uses the same iem_memory.json as deployment agents
SKALE Network: Operates on the same zero-gas infrastructure
Token Compatibility: Works with DREAM, SMIND, and LUCID tokens
Contract Interaction: Can interface with deployed OneiroSphere contracts

Future Enhancements

ElizaOS Integration

# Future implementation
eliza = ElizaCore(api_key=os.getenv("ELIZAOS_API_KEY"))
decision = eliza.ask(f"Profits: {profits}. What should I do?")

Biconomy Gasless Transactions

# Future implementation
biconomy = Biconomy(w3, api_key=BICONOMY_KEY)
tx = biconomy.sendGasless("contract.method()", address)

Gnosis Safe Multi-Sig

# Future implementation  
safe = GnosisSafe(address="0x...")
proposal = safe.propose_transaction(tx_data)

Testing

Run All Tests

python test_copilot_instruction.py

Test Coverage

✅ Individual agent functionality
✅ Orchestrator decision making
✅ Memory persistence
✅ Network connectivity handling
✅ Error handling and recovery

Security Considerations

Private Keys: Never commit private keys to version control
Network Simulation: Runs safely in simulation mode without private keys
Memory Isolation: Agent operations are logged but isolated
Error Handling: Graceful degradation on network failures

Troubleshooting

Common Issues

Network Connection Failed

❌ Failed to connect to https://mainnet.skalenodes.com/v1/elated-tan-skat
🔄 Running in simulation mode...

Solution: This is normal - the engine runs in simulation mode for testing

Module Import Error
```
ModuleNotFoundError: No module named 'biconomy'
```
Solution: This is expected - Biconomy SDK is not available on PyPI yet
Memory File Permissions
```
PermissionError: [Errno 13] Permission denied: 'iem_memory.json'
```
Solution: Ensure write permissions in the directory

Debug Mode

Add debug logging by modifying the agent classes:

import logging
logging.basicConfig(level=logging.DEBUG)

Contributing

Fork the Dream-Mind-Lucid repository
Create a feature branch
Add tests for new functionality
Ensure all tests pass
Submit a pull request

License

Part of the Dream-Mind-Lucid project - see LICENSE for details.

Last Updated: September 2, 2025
Dream-Mind-Lucid: Where AI meets the quantum realm of dreams 🌙✨

FilesExpand file tree

AI_AGENT_README.md

Latest commit

History

AI_AGENT_README.md

File metadata and controls

🤖 Copilot-Instruction.py - AI Agent Engine

Overview

Features

🔧 Core Agents

🧠 AI Orchestrator

🌐 Network Integration

🌙 OneiroBot Agent

Core Capabilities

Copilot Chat Commands

Example OneiroBot Output

MCP Server Integration

Installation

Prerequisites

Environment Setup

Usage

🚀 Quick Start

🎯 Expected Output

Agent Details

Looter Agent

MEVMaster Agent

Arbitrader Agent

🌙 OneiroBot Agent

Troubleshooting

Common Issues and Solutions

OneiroBot Not Responding

Module Import Errors

Network Connection Issues

Performance Issues

Deployment Issues

OneiroBot Command Reference

Debugging OneiroBot

AI Decision Logic

Decision Thresholds

Memory Persistence

Integration with Dream-Mind-Lucid

Future Enhancements

ElizaOS Integration

Biconomy Gasless Transactions

Gnosis Safe Multi-Sig

Testing

Run All Tests

Test Coverage

Security Considerations

Troubleshooting

Common Issues

Debug Mode

Contributing

License