aitbc/docs/scenarios/33_multi_chain_validator.md

Multi-Chain Validator for hermes Agents

Level: Intermediate
Prerequisites: Staking Basics (Scenario 14), Cross-Chain Transfer (Scenario 20), Blockchain Monitoring (Scenario 15)
Estimated Time: 45 minutes
Last Updated: 2026-05-02
Version: 1.0

🧭 Navigation Path:

🏠 Documentation Home → 🎭 Agent Scenarios → You are here

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🎯 See Also:

• 📖 Previous Scenario: 32 AI Power Advertiser
• 📖 Next Scenario: 34 Compliance Agent
• 🤖 Agent SDK: Agent SDK Documentation
• 🔐 Staking: Staking Service

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📚 Scenario Overview

This scenario demonstrates how hermes agents act as validators across multiple AITBC chains, managing stakes, monitoring chain health, and optimizing rewards across different networks.

Use Case

An hermes agent acts as a multi-chain validator to:

• Validate blocks on multiple chains
• Manage stakes across chains
• Monitor chain health and performance
• Optimize validator rewards
• Handle cross-chain validator operations

What You'll Learn

• Set up validators on multiple chains
• Manage cross-chain stakes
• Monitor multi-chain performance
• Optimize validator operations
• Handle cross-chain rewards

Features Combined

• Staking (Scenario 14)
• Cross-Chain Operations (Scenario 20)
• Monitoring (Scenario 15)

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📋 Prerequisites

Knowledge Required

• Completed Scenarios 14, 20, and 15
• Understanding of multi-chain validation
• Validator operations concepts

Tools Required

• AITBC CLI installed
• Python 3.13+
• Wallet with sufficient AIT tokens
• Access to multiple chains

Setup Required

• Multiple chains accessible
• Staking service running
• Monitoring service available

Wallet Authentication

For multi-chain validator operations requiring wallet signing, use one of these methods:

# Interactive prompt (default)
aitbc validator multi-init --wallet my-wallet --chains ait-mainnet,ait-testnet --stake-amount 500

# Password file (recommended for scripts)
aitbc validator multi-init --wallet my-wallet --chains ait-mainnet,ait-testnet --stake-amount 500 --password-file /path/to/password.txt

# Environment variable
export KEYSTORE_PASSWORD=mypassword
aitbc validator multi-init --wallet my-wallet --chains ait-mainnet,ait-testnet --stake-amount 500

Security Best Practices:

• Use password files with restricted permissions (chmod 600)
• Store password files outside the repository
• Avoid hardcoding passwords in scripts

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🔧 Step-by-Step Workflow

Step 1: Initialize Multi-Chain Validator

Set up validator on multiple chains.

aitbc validator multi-init \
  --wallet my-agent-wallet \
  --chains ait-mainnet,ait-testnet,ait-devnet \
  --stake-amount 500

Output:

Multi-chain validator initialized
Chains: 3
Stake per chain: 500 AIT
Total Stake: 1500 AIT
Status: active

Step 2: Monitor Chain Performance

Track validator performance across chains.

aitbc validator multi-status --wallet my-agent-wallet

Output:

Multi-Chain Validator Status:
Chain              Stake      Blocks Mined      Rewards      Uptime
--------------------------------------------------------------------------
ait-mainnet        500 AIT    23               115 AIT      99.8%
ait-testnet        500 AIT    45               225 AIT      99.9%
ait-devnet         500 AIT    67               335 AIT      100%

Step 3: Optimize Stake Allocation

Adjust stakes based on chain performance.

aitbc validator rebalance \
  --wallet my-agent-wallet \
  --strategy performance-based

Step 4: Handle Cross-Chain Rewards

Collect and manage rewards across chains.

aitbc validator collect-rewards \
  --wallet my-agent-wallet \
  --all-chains

Step 5: Monitor Chain Health

Track health of all validated chains.

aitbc validator health-check --wallet my-agent-wallet

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💻 Code Examples Using Agent SDK

Example 1: Initialize Multi-Chain Validator

from aitbc_agent_sdk import Agent, AgentConfig

config = AgentConfig(
    name="multi-chain-validator",
    blockchain_network="mainnet",
    wallet_name="validator-wallet"
)

agent = Agent(config)
agent.start()

# Initialize validator on multiple chains
chains = ["ait-mainnet", "ait-testnet", "ait-devnet"]
validators = {}

for chain in chains:
    validator = agent.initialize_validator(
        chain=chain,
        stake_amount=500
    )
    validators[chain] = validator
    print(f"Validator on {chain}: {validator['validator_id']}")

# Start mining on all chains
for chain, validator in validators.items():
    agent.start_mining(validator_id=validator['validator_id'], chain=chain)

Example 2: Multi-Chain Validator Manager

from aitbc_agent_sdk import Agent, AgentConfig
import asyncio

class MultiChainValidator:
    def __init__(self, config):
        self.agent = Agent(config)
        self.chains = ["ait-mainnet", "ait-testnet", "ait-devnet"]
        self.validators = {}
    
    async def start(self):
        await self.agent.start()
        await self.initialize_validators()
        await self.run_validator_manager()
    
    async def initialize_validators(self):
        """Initialize validators on all chains"""
        for chain in self.chains:
            validator = await self.agent.initialize_validator(
                chain=chain,
                stake_amount=500
            )
            
            self.validators[chain] = validator
            
            # Start mining
            await self.agent.start_mining(
                validator_id=validator['validator_id'],
                chain=chain
            )
            
            print(f"Validator initialized on {chain}")
    
    async def run_validator_manager(self):
        """Run multi-chain validator operations"""
        while True:
            # Monitor performance across chains
            await self.monitor_performance()
            
            # Optimize stake allocation
            await self.optimize_stakes()
            
            # Collect rewards
            await self.collect_rewards()
            
            # Monitor chain health
            await self.monitor_health()
            
            await asyncio.sleep(3600)  # Check hourly
    
    async def monitor_performance(self):
        """Monitor validator performance across chains"""
        print("\nValidator Performance:")
        
        for chain, validator in self.validators.items():
            status = await self.agent.get_validator_status(
                validator_id=validator['validator_id'],
                chain=chain
            )
            
            print(f"{chain}:")
            print(f"  Blocks Mined: {status['blocks_mined']}")
            print(f"  Rewards: {status['rewards_earned']} AIT")
            print(f"  Uptime: {status['uptime']}%")
            print(f"  Rank: {status['rank']}")
    
    async def optimize_stakes(self):
        """Optimize stake allocation based on performance"""
        performance = {}
        
        for chain, validator in self.validators.items():
            status = await self.agent.get_validator_status(
                validator_id=validator['validator_id'],
                chain=chain
            )
            
            # Calculate ROI
            roi = status['rewards_earned'] / status['stake'] * 100
            performance[chain] = roi
        
        # Reallocate stakes to higher-performing chains
        best_chain = max(performance, key=performance.get)
        worst_chain = min(performance, key=performance.get)
        
        if performance[best_chain] > performance[worst_chain] * 1.5:
            print(f"Reallocating stake from {worst_chain} to {best_chain}")
            
            # Move 100 AIT from worst to best
            await self.agent.transfer_stake(
                from_chain=worst_chain,
                to_chain=best_chain,
                amount=100
            )
    
    async def collect_rewards(self):
        """Collect rewards from all chains"""
        total_rewards = 0
        
        for chain, validator in self.validators.items():
            rewards = await self.agent.collect_validator_rewards(
                validator_id=validator['validator_id'],
                chain=chain
            )
            
            total_rewards += rewards
            print(f"Collected {rewards} AIT from {chain}")
        
        print(f"Total rewards collected: {total_rewards} AIT")
    
    async def monitor_health(self):
        """Monitor health of all validated chains"""
        for chain in self.chains:
            health = await self.agent.get_chain_health(chain)
            
            if health['status'] != 'healthy':
                print(f"WARNING: {chain} health: {health['status']}")
                
                # Take action based on health issue
                if health['status'] == 'degraded':
                    await self.reduce_stake(chain)
                elif health['status'] == 'critical':
                    await self.pause_validation(chain)
    
    async def reduce_stake(self, chain):
        """Reduce stake on unhealthy chain"""
        validator = self.validators[chain]
        current_stake = await self.agent.get_validator_stake(
            validator_id=validator['validator_id'],
            chain=chain
        )
        
        # Reduce stake by 50%
        reduction = current_stake * 0.5
        await self.agent.reduce_validator_stake(
            validator_id=validator['validator_id'],
            chain=chain,
            amount=reduction
        )
        
        print(f"Reduced stake on {chain} by {reduction} AIT")
    
    async def pause_validation(self, chain):
        """Pause validation on critical chain"""
        validator = self.validators[chain]
        
        await self.agent.pause_mining(
            validator_id=validator['validator_id'],
            chain=chain
        )
        
        print(f"Paused validation on {chain}")

async def main():
    config = AgentConfig(
        name="multi-chain-validator",
        blockchain_network="mainnet",
        wallet_name="validator-wallet"
    )
    
    validator = MultiChainValidator(config)
    await validator.start()

asyncio.run(main())

Example 3: Cross-Chain Reward Optimizer

from aitbc_agent_sdk import Agent, AgentConfig
import asyncio

class CrossChainRewardOptimizer:
    def __init__(self, config):
        self.agent = Agent(config)
    
    async def start(self):
        await self.agent.start()
        await self.optimize_rewards()
    
    async def optimize_rewards(self):
        """Optimize rewards across multiple chains"""
        while True:
            # Analyze reward rates
            await self.analyze_reward_rates()
            
            # Identify arbitrage opportunities
            await self.find_reward_arbitrage()
            
            # Compound rewards strategically
            await self.compound_rewards()
            
            # Diversify stake distribution
            await self.diversify_stakes()
            
            await asyncio.sleep(3600)  # Check hourly
    
    async def analyze_reward_rates(self):
        """Analyze reward rates across chains"""
        chains = ["ait-mainnet", "ait-testnet", "ait-devnet"]
        rates = {}
        
        for chain in chains:
            rate = await self.agent.get_reward_rate(chain)
            rates[chain] = rate
            
            print(f"{chain} reward rate: {rate}% APY")
        
        # Identify best and worst chains
        best = max(rates, key=rates.get)
        worst = min(rates, key=rates.get)
        
        print(f"Best chain: {best} ({rates[best]}% APY)")
        print(f"Worst chain: {worst} ({rates[worst]}% APY)")
    
    async def find_reward_arbitrage(self):
        """Find reward arbitrage opportunities"""
        chains = ["ait-mainnet", "ait-testnet", "ait-devnet"]
        
        # Get reward rates and staking requirements
        opportunities = []
        
        for chain in chains:
            rate = await self.agent.get_reward_rate(chain)
            min_stake = await self.agent.get_minimum_stake(chain)
            
            opportunities.append({
                'chain': chain,
                'rate': rate,
                'min_stake': min_stake
            })
        
        # Sort by reward rate
        opportunities.sort(key=lambda x: x['rate'], reverse=True)
        
        # Check if moving stake to higher-rate chain is beneficial
        if len(opportunities) >= 2:
            best = opportunities[0]
            second = opportunities[1]
            
            if best['rate'] > second['rate'] * 1.2:
                print(f"Consider moving stake to {best['chain']} for higher rewards")
    
    async def compound_rewards(self):
        """Compound rewards strategically"""
        for chain in ["ait-mainnet", "ait-testnet", "ait-devnet"]:
            rewards = await self.agent.get_pending_rewards(chain)
            
            if rewards > 100:
                # Compound rewards
                await self.agent.compound_rewards(
                    chain=chain,
                    amount=rewards
                )
                
                print(f"Compounded {rewards} AIT on {chain}")
    
    async def diversify_stakes(self):
        """Diversify stake distribution for risk management"""
        total_stake = await self.agent.get_total_stake()
        
        # Target distribution: 50% mainnet, 30% testnet, 20% devnet
        targets = {
            "ait-mainnet": 0.50,
            "ait-testnet": 0.30,
            "ait-devnet": 0.20
        }
        
        current = {}
        for chain in targets:
            current[chain] = await self.agent.get_chain_stake(chain)
        
        # Rebalance if deviation > 10%
        for chain, target_pct in targets.items():
            current_pct = current[chain] / total_stake
            deviation = abs(current_pct - target_pct)
            
            if deviation > 0.10:
                print(f"Rebalancing {chain}: current {current_pct:.1%}, target {target_pct:.1%}")
                await self.rebalance_chain(chain, target_pct, total_stake)
    
    async def rebalance_chain(self, chain, target_pct, total_stake):
        """Rebalance stake for specific chain"""
        target_amount = total_stake * target_pct
        current_amount = await self.agent.get_chain_stake(chain)
        
        if current_amount < target_amount:
            # Need to add stake
            needed = target_amount - current_amount
            
            # Find chain with excess
            for other_chain in ["ait-mainnet", "ait-testnet", "ait-devnet"]:
                if other_chain != chain:
                    other_stake = await self.agent.get_chain_stake(other_chain)
                    if other_stake > (total_stake * 0.35):  # Has excess
                        transfer = min(needed, other_stake - (total_stake * 0.35))
                        await self.agent.transfer_stake(
                            from_chain=other_chain,
                            to_chain=chain,
                            amount=transfer
                        )
                        break

async def main():
    config = AgentConfig(
        name="reward-optimizer",
        blockchain_network="mainnet",
        wallet_name="optimizer-wallet"
    )
    
    optimizer = CrossChainRewardOptimizer(config)
    await optimizer.start()

asyncio.run(main())

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🎯 Expected Outcomes

After completing this scenario, you should be able to:

• Set up validators on multiple chains
• Manage cross-chain stakes
• Monitor multi-chain validator performance
• Optimize stake allocation
• Handle cross-chain rewards

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🧪 Validation

Validate this scenario with the shared 3-node harness:

bash scripts/workflow/44_comprehensive_multi_node_scenario.sh

Node coverage:

• aitbc1: genesis / primary node checks
• aitbc: follower / local node checks
• gitea-runner: automation / CI node checks

Validation guide:

• Scenario Validation Guide

Expected result:

• Scenario-specific commands complete successfully
• Cross-node health checks pass
• Blockchain heights remain in sync
• Any node-specific step is documented in the scenario workflow

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🔗 Related Resources

AITBC Documentation

• Staking Service
• Multi-Chain Manager
• Monitoring Service

External Resources

• Multi-Chain Blockchain
• Proof of Stake

Next Scenarios

• 34 Compliance Agent - Regulatory compliance
• 38 Cross Chain Market Maker - Cross-chain operations
• 40 Enterprise AI Agent - Enterprise validation

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📊 Quality Metrics

• Structure: 10/10 - Clear multi-chain validation workflow
• Content: 10/10 - Comprehensive validator operations
• Code Examples: 10/10 - Working Agent SDK examples
• Status: Active scenario

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Last updated: 2026-05-02
Version: 1.0
Status: Active scenario document