// Core agent state management
#[derive(Clone, Debug, Serialize, Deserialize)]
pub struct AgentState {
    // Identity and configuration
    pub id: AgentId,
    pub did: String,
    pub agent_type: AgentType,
    pub capabilities: Vec<Capability>,
    
    // Financial state
    pub wallet: WalletState,
    pub treasury: TreasuryState,
    pub spending_history: Vec<Transaction>,
    
    // Operational state
    pub tasks: VecDeque<Task>,
    pub goals: Vec<Goal>,
    pub memory: AgentMemory,
    pub context: ExecutionContext,
    
    // Network state
    pub connections: HashMap<String, ConnectionState>,
    pub reputation: ReputationScore,
    pub performance_metrics: PerformanceMetrics,
    
    // Security state
    pub permissions: PermissionSet,
    pub audit_trail: Vec<AuditEvent>,
    pub risk_assessment: RiskAssessment,
}

impl AgentState {
    pub fn new(config: AgentConfig) -> Self {
        Self {
            id: AgentId::generate(),
            did: format!("did:stateset:agent:{}", Uuid::new_v4()),
            agent_type: config.agent_type,
            capabilities: config.capabilities,
            wallet: WalletState::new(config.initial_balance),
            treasury: TreasuryState::new(),
            spending_history: Vec::new(),
            tasks: VecDeque::new(),
            goals: config.initial_goals,
            memory: AgentMemory::new(),
            context: ExecutionContext::default(),
            connections: HashMap::new(),
            reputation: ReputationScore::new(),
            performance_metrics: PerformanceMetrics::new(),
            permissions: config.permissions,
            audit_trail: Vec::new(),
            risk_assessment: RiskAssessment::new(),
        }
    }
    
    pub async fn execute_cycle(&mut self) -> Result<ExecutionResult> {
        // 1. Perception: Gather information
        let perception = self.perceive_environment().await?;
        
        // 2. Cognition: Process and decide
        let decisions = self.make_decisions(perception).await?;
        
        // 3. Action: Execute decisions
        let actions = self.execute_actions(decisions).await?;
        
        // 4. Learning: Update state based on results
        self.learn_from_results(actions).await?;
        
        Ok(ExecutionResult { actions })
    }
}

// Agent decision-making system
pub struct CognitiveEngine {
    reasoning_engine: ReasoningEngine,
    learning_system: LearningSystem,
    goal_planner: GoalPlanner,
    memory_manager: MemoryManager,
}

impl CognitiveEngine {
    pub async fn make_decision(
        &self,
        context: &ExecutionContext,
        goals: &[Goal],
        constraints: &[Constraint],
    ) -> Result<Decision> {
        // Multi-step reasoning process
        let options = self.generate_options(context, goals).await?;
        let filtered_options = self.apply_constraints(options, constraints)?;
        let evaluated_options = self.evaluate_options(filtered_options).await?;
        let best_option = self.select_best_option(evaluated_options)?;
        
        // Create decision with rationale
        Ok(Decision {
            action: best_option.action,
            confidence: best_option.confidence,
            rationale: best_option.reasoning,
            risk_assessment: best_option.risks,
            expected_outcome: best_option.expected_outcome,
        })
    }
    
    async fn generate_options(
        &self,
        context: &ExecutionContext,
        goals: &[Goal],
    ) -> Result<Vec<ActionOption>> {
        let mut options = Vec::new();
        
        // Generate options for each goal
        for goal in goals {
            let goal_options = match goal.goal_type {
                GoalType::Financial => self.generate_financial_options(context, goal).await?,
                GoalType::Operational => self.generate_operational_options(context, goal).await?,
                GoalType::Strategic => self.generate_strategic_options(context, goal).await?,
            };
            options.extend(goal_options);
        }
        
        Ok(options)
    }
}

// Native USDC wallet for autonomous agents
pub struct AgentWallet {
    address: String,
    private_key: SecretKey,
    balance: Balance,
    transaction_history: Vec<Transaction>,
    spending_limits: SpendingLimits,
    multi_sig_config: Option<MultiSigConfig>,
    treasury_strategy: TreasuryStrategy,
}

impl AgentWallet {
    pub async fn new(config: WalletConfig) -> Result<Self> {
        let (private_key, public_key) = generate_keypair();
        let address = derive_address(&public_key);
        
        Ok(Self {
            address,
            private_key,
            balance: Balance::new(),
            transaction_history: Vec::new(),
            spending_limits: config.spending_limits,
            multi_sig_config: config.multi_sig,
            treasury_strategy: config.treasury_strategy,
        })
    }
    
    pub async fn execute_payment(
        &mut self,
        recipient: &str,
        amount: &str,
        memo: Option<String>,
    ) -> Result<TransactionResult> {
        // Pre-transaction validation
        self.validate_payment(recipient, amount).await?;
        
        // Check spending limits
        self.check_spending_limits(amount)?;
        
        // Execute transaction on StateSet network
        let tx = Transaction {
            from: self.address.clone(),
            to: recipient.to_string(),
            amount: amount.parse()?,
            memo,
            timestamp: Utc::now(),
        };
        
        let signed_tx = self.sign_transaction(&tx)?;
        let result = self.broadcast_transaction(signed_tx).await?;
        
        // Update local state
        self.balance.subtract(amount.parse()?)?;
        self.transaction_history.push(tx);
        
        Ok(result)
    }
    
    pub async fn optimize_treasury(&mut self) -> Result<OptimizationResult> {
        match &self.treasury_strategy {
            TreasuryStrategy::Conservative => self.conservative_optimization().await,
            TreasuryStrategy::Balanced => self.balanced_optimization().await,
            TreasuryStrategy::Aggressive => self.aggressive_optimization().await,
        }
    }
    
    async fn balanced_optimization(&mut self) -> Result<OptimizationResult> {
        let current_balance = self.balance.usdc.clone();
        let target_allocation = self.calculate_target_allocation(&current_balance).await?;
        
        let mut actions = Vec::new();
        
        // Staking allocation (40% of idle funds)
        if target_allocation.staking > 0 {
            actions.push(TreasuryAction::Stake {
                amount: target_allocation.staking,
                validator: self.select_validator().await?,
                duration: Duration::days(30),
            });
        }
        
        // Liquidity provision (30% of idle funds)
        if target_allocation.liquidity > 0 {
            actions.push(TreasuryAction::ProvideLiquidity {
                pool: "USDC/STATE".to_string(),
                amount: target_allocation.liquidity,
                min_apr: 0.05, // 5% minimum APR
            });
        }
        
        // Keep 30% liquid for operations
        
        // Execute treasury actions
        for action in &actions {
            self.execute_treasury_action(action).await?;
        }
        
        Ok(OptimizationResult { actions })
    }
}

// Multi-signature wallet for high-value agent operations
pub struct MultiSigAgentWallet {
    threshold: u8,
    signers: Vec<AgentSigner>,
    pending_transactions: HashMap<String, PendingTransaction>,
    execution_policy: ExecutionPolicy,
}

impl MultiSigAgentWallet {
    pub async fn propose_transaction(
        &mut self,
        transaction: Transaction,
        proposer: AgentId,
    ) -> Result<ProposalId> {
        let proposal_id = Uuid::new_v4().to_string();
        
        // Create pending transaction
        let pending = PendingTransaction {
            id: proposal_id.clone(),
            transaction,
            proposer,
            signatures: Vec::new(),
            created_at: Utc::now(),
            expires_at: Utc::now() + Duration::hours(24),
        };
        
        self.pending_transactions.insert(proposal_id.clone(), pending);
        
        // Notify other signers
        for signer in &self.signers {
            self.notify_signer(signer, &proposal_id).await?;
        }
        
        Ok(proposal_id)
    }
    
    pub async fn sign_transaction(
        &mut self,
        proposal_id: &str,
        signer: AgentId,
        signature: Signature,
    ) -> Result<SignatureResult> {
        let pending = self.pending_transactions
            .get_mut(proposal_id)
            .ok_or(Error::ProposalNotFound)?;
        
        // Verify signature
        self.verify_signature(&pending.transaction, &signature, &signer)?;
        
        // Add signature
        pending.signatures.push(AgentSignature {
            signer,
            signature,
            signed_at: Utc::now(),
        });
        
        // Check if threshold reached
        if pending.signatures.len() >= self.threshold as usize {
            let result = self.execute_transaction(pending).await?;
            self.pending_transactions.remove(proposal_id);
            Ok(SignatureResult::Executed(result))
        } else {
            Ok(SignatureResult::SignatureAdded)
        }
    }
}

// Model Context Protocol gateway for cross-web interactions
pub struct MCPGateway {
    connections: HashMap<String, MCPConnection>,
    protocol_router: ProtocolRouter,
    state_synchronizer: StateSynchronizer,
    event_bus: EventBus,
}

impl MCPGateway {
    pub async fn connect_to_service(
        &mut self,
        service_name: &str,
        config: ServiceConfig,
    ) -> Result<ConnectionId> {
        let connection = MCPConnection::new(service_name, config).await?;
        let connection_id = connection.id.clone();
        
        // Establish bidirectional communication
        connection.handshake().await?;
        
        // Register available tools and resources
        let tools = connection.list_tools().await?;
        let resources = connection.list_resources().await?;
        
        self.protocol_router.register_service(service_name, tools, resources)?;
        self.connections.insert(connection_id.clone(), connection);
        
        Ok(connection_id)
    }
    
    pub async fn execute_cross_platform_action(
        &self,
        service: &str,
        action: CrossPlatformAction,
    ) -> Result<ActionResult> {
        let connection = self.connections
            .get(service)
            .ok_or(Error::ServiceNotConnected)?;
        
        match action {
            CrossPlatformAction::ReadResource { name, args } => {
                self.read_resource(connection, &name, args).await
            },
            CrossPlatformAction::CallTool { name, args } => {
                self.call_tool(connection, &name, args).await
            },
            CrossPlatformAction::UpdateState { path, value } => {
                self.update_state(connection, &path, value).await
            },
        }
    }
    
    async fn call_tool(
        &self,
        connection: &MCPConnection,
        tool_name: &str,
        args: serde_json::Value,
    ) -> Result<ActionResult> {
        // Prepare MCP tool call message
        let request = MCPRequest::CallTool {
            name: tool_name.to_string(),
            arguments: args,
        };
        
        // Send request through connection
        let response = connection.send_request(request).await?;
        
        // Process response
        match response {
            MCPResponse::ToolResult { content, is_error } => {
                if is_error {
                    Err(Error::ToolExecutionFailed(content))
                } else {
                    Ok(ActionResult::Success { data: content })
                }
            },
            _ => Err(Error::UnexpectedResponse),
        }
    }
}

// State synchronization across web platforms
pub struct CrossWebStateManager {
    local_state: AgentState,
    remote_states: HashMap<String, RemoteState>,
    sync_policies: Vec<SyncPolicy>,
    conflict_resolver: ConflictResolver,
}

impl CrossWebStateManager {
    pub async fn sync_state_across_platforms(
        &mut self,
        platforms: Vec<String>,
    ) -> Result<SyncResult> {
        let mut sync_operations = Vec::new();
        
        for platform in platforms {
            // Get current state from platform
            let remote_state = self.get_remote_state(&platform).await?;
            
            // Detect conflicts
            let conflicts = self.detect_conflicts(&platform, &remote_state)?;
            
            if !conflicts.is_empty() {
                // Resolve conflicts using configured strategy
                let resolutions = self.conflict_resolver.resolve(conflicts).await?;
                sync_operations.extend(resolutions);
            }
            
            // Generate sync operations
            let platform_ops = self.generate_sync_operations(&platform, &remote_state)?;
            sync_operations.extend(platform_ops);
        }
        
        // Execute all sync operations atomically
        self.execute_sync_operations(sync_operations).await
    }
    
    async fn propagate_state_change(
        &self,
        change: StateChange,
        target_platforms: Vec<String>,
    ) -> Result<PropagationResult> {
        let mut results = Vec::new();
        
        for platform in target_platforms {
            match self.apply_change_to_platform(&platform, &change).await {
                Ok(result) => results.push(PlatformResult::Success(result)),
                Err(error) => results.push(PlatformResult::Error(error)),
            }
        }
        
        Ok(PropagationResult { results })
    }
}

// Specific adapters for different platforms
pub trait PlatformAdapter {
    async fn authenticate(&self, credentials: Credentials) -> Result<AuthToken>;
    async fn read_data(&self, resource: &str) -> Result<serde_json::Value>;
    async fn write_data(&self, resource: &str, data: serde_json::Value) -> Result<WriteResult>;
    async fn execute_action(&self, action: PlatformAction) -> Result<ActionResult>;
    async fn subscribe_to_events(&self, events: Vec<String>) -> Result<EventStream>;
}

// Salesforce adapter
pub struct SalesforceAdapter {
    base_url: String,
    auth_token: Option<String>,
    http_client: HttpClient,
}

impl PlatformAdapter for SalesforceAdapter {
    async fn execute_action(&self, action: PlatformAction) -> Result<ActionResult> {
        match action {
            PlatformAction::CreateLead { name, email, company } => {
                let payload = json!({
                    "FirstName": name.split_whitespace().next().unwrap_or(""),
                    "LastName": name.split_whitespace().last().unwrap_or(""),
                    "Email": email,
                    "Company": company
                });
                
                self.salesforce_api_call("POST", "/services/data/v58.0/sobjects/Lead/", payload).await
            },
            PlatformAction::UpdateOpportunity { id, stage, amount } => {
                let payload = json!({
                    "StageName": stage,
                    "Amount": amount
                });
                
                self.salesforce_api_call(
                    "PATCH", 
                    &format!("/services/data/v58.0/sobjects/Opportunity/{}", id), 
                    payload
                ).await
            },
            _ => Err(Error::UnsupportedAction),
        }
    }
}

// SAP adapter
pub struct SAPAdapter {
    base_url: String,
    username: String,
    password: String,
    csrf_token: Option<String>,
}

impl PlatformAdapter for SAPAdapter {
    async fn execute_action(&self, action: PlatformAction) -> Result<ActionResult> {
        match action {
            PlatformAction::CreatePurchaseOrder { vendor, items, total } => {
                let payload = json!({
                    "PurchasingDocument": "",
                    "PurchasingDocumentType": "NB",
                    "Supplier": vendor,
                    "PurchasingDocumentItem": items.iter().map(|item| json!({
                        "Material": item.material,
                        "OrderQuantity": item.quantity,
                        "NetAmount": item.price
                    })).collect::<Vec<_>>()
                });
                
                self.sap_api_call("POST", "/sap/opu/odata/sap/MM_PUR_PO_MAINTAIN_SRV/C_PurchaseOrderTP", payload).await
            },
            _ => Err(Error::UnsupportedAction),
        }
    }
}

// Communication protocol between agents
#[derive(Clone, Debug, Serialize, Deserialize)]
pub struct AgentMessage {
    pub id: String,
    pub from: AgentId,
    pub to: AgentId,
    pub message_type: MessageType,
    pub payload: serde_json::Value,
    pub timestamp: DateTime<Utc>,
    pub signature: String,
    pub priority: Priority,
}

#[derive(Clone, Debug, Serialize, Deserialize)]
pub enum MessageType {
    Request(RequestType),
    Response(ResponseType),
    Notification(NotificationType),
    Broadcast(BroadcastType),
}

pub struct AgentCommunicationHub {
    message_router: MessageRouter,
    subscription_manager: SubscriptionManager,
    encryption_service: EncryptionService,
    reputation_tracker: ReputationTracker,
}

impl AgentCommunicationHub {
    pub async fn send_message(
        &self,
        message: AgentMessage,
    ) -> Result<MessageResult> {
        // Validate message
        self.validate_message(&message)?;
        
        // Encrypt if required
        let encrypted_message = if self.requires_encryption(&message) {
            self.encryption_service.encrypt(message).await?
        } else {
            message
        };
        
        // Route message
        let result = self.message_router.route(encrypted_message).await?;
        
        // Update reputation based on result
        self.reputation_tracker.update_from_message_result(&result).await?;
        
        Ok(result)
    }
    
    pub async fn broadcast_to_network(
        &self,
        sender: AgentId,
        broadcast: BroadcastMessage,
        filters: Vec<AgentFilter>,
    ) -> Result<BroadcastResult> {
        // Find matching agents
        let recipients = self.find_agents_matching_filters(filters).await?;
        
        // Create individual messages
        let messages: Vec<AgentMessage> = recipients
            .into_iter()
            .map(|recipient| AgentMessage {
                id: Uuid::new_v4().to_string(),
                from: sender,
                to: recipient,
                message_type: MessageType::Broadcast(broadcast.broadcast_type.clone()),
                payload: broadcast.payload.clone(),
                timestamp: Utc::now(),
                signature: String::new(), // Will be signed later
                priority: broadcast.priority,
            })
            .collect();
        
        // Send all messages
        let results = futures::future::join_all(
            messages.into_iter().map(|msg| self.send_message(msg))
        ).await;
        
        Ok(BroadcastResult {
            total_sent: results.len(),
            successful: results.iter().filter(|r| r.is_ok()).count(),
            failed: results.iter().filter(|r| r.is_err()).count(),
        })
    }
}

// Agent discovery and coordination system
pub struct AgentDiscoveryService {
    agent_registry: AgentRegistry,
    capability_index: CapabilityIndex,
    reputation_service: ReputationService,
    coordination_engine: CoordinationEngine,
}

impl AgentDiscoveryService {
    pub async fn find_agents_by_capability(
        &self,
        capability: Capability,
        requirements: Requirements,
    ) -> Result<Vec<AgentDescriptor>> {
        // Query capability index
        let candidate_agents = self.capability_index
            .find_by_capability(capability)
            .await?;
        
        // Filter by requirements
        let filtered_agents = self.filter_agents_by_requirements(
            candidate_agents,
            requirements
        ).await?;
        
        // Sort by reputation and performance
        let mut sorted_agents = self.sort_agents_by_suitability(filtered_agents).await?;
        
        Ok(sorted_agents)
    }
    
    pub async fn coordinate_multi_agent_task(
        &self,
        task: ComplexTask,
        coordination_strategy: CoordinationStrategy,
    ) -> Result<CoordinationPlan> {
        // Break down task into subtasks
        let subtasks = self.decompose_task(task).await?;
        
        // Find suitable agents for each subtask
        let mut agent_assignments = Vec::new();
        
        for subtask in subtasks {
            let suitable_agents = self.find_agents_by_capability(
                subtask.required_capability,
                subtask.requirements
            ).await?;
            
            if suitable_agents.is_empty() {
                return Err(Error::NoSuitableAgents);
            }
            
            agent_assignments.push(AgentAssignment {
                subtask,
                assigned_agent: suitable_agents[0].clone(),
                backup_agents: suitable_agents[1..].to_vec(),
            });
        }
        
        // Create coordination plan
        let plan = self.coordination_engine.create_plan(
            agent_assignments,
            coordination_strategy
        ).await?;
        
        Ok(plan)
    }
}

// Governance framework for autonomous agent decisions
pub struct AgentGovernance {
    decision_rules: Vec<DecisionRule>,
    approval_workflows: HashMap<ActionType, ApprovalWorkflow>,
    risk_assessor: RiskAssessor,
    compliance_checker: ComplianceChecker,
}

impl AgentGovernance {
    pub async fn evaluate_proposed_action(
        &self,
        agent_id: AgentId,
        proposed_action: ProposedAction,
    ) -> Result<ActionApproval> {
        // Risk assessment
        let risk_assessment = self.risk_assessor
            .assess_action_risk(&proposed_action)
            .await?;
        
        // Compliance check
        let compliance_result = self.compliance_checker
            .check_compliance(&proposed_action)
            .await?;
        
        // Apply decision rules
        let rule_evaluation = self.apply_decision_rules(
            &proposed_action,
            &risk_assessment,
            &compliance_result
        )?;
        
        // Determine if approval workflow is required
        if let Some(workflow) = self.approval_workflows.get(&proposed_action.action_type) {
            if rule_evaluation.requires_approval {
                return self.initiate_approval_workflow(
                    workflow,
                    proposed_action,
                    rule_evaluation
                ).await;
            }
        }
        
        // Auto-approve if within parameters
        if rule_evaluation.auto_approve {
            Ok(ActionApproval::Approved {
                conditions: rule_evaluation.conditions,
                monitoring_required: rule_evaluation.monitoring_required,
            })
        } else {
            Ok(ActionApproval::Denied {
                reason: rule_evaluation.denial_reason,
                alternative_actions: rule_evaluation.alternatives,
            })
        }
    }
    
    async fn initiate_approval_workflow(
        &self,
        workflow: &ApprovalWorkflow,
        action: ProposedAction,
        evaluation: RuleEvaluation,
    ) -> Result<ActionApproval> {
        // Create approval request
        let approval_request = ApprovalRequest {
            id: Uuid::new_v4().to_string(),
            action,
            evaluation,
            created_at: Utc::now(),
            expires_at: Utc::now() + workflow.timeout,
        };
        
        // Send to approvers
        for approver in &workflow.approvers {
            self.send_approval_request(approver, &approval_request).await?;
        }
        
        Ok(ActionApproval::PendingApproval {
            request_id: approval_request.id,
            required_approvals: workflow.required_approvals,
            timeout: workflow.timeout,
        })
    }
}

// Reputation system for agent network
pub struct AgentReputationSystem {
    reputation_scores: HashMap<AgentId, ReputationScore>,
    interaction_history: Vec<AgentInteraction>,
    reputation_calculator: ReputationCalculator,
    stake_manager: StakeManager,
}

#[derive(Clone, Debug)]
pub struct ReputationScore {
    pub overall_score: f64,        // 0-100
    pub reliability: f64,          // Task completion rate
    pub efficiency: f64,           // Cost-effectiveness
    pub cooperation: f64,          // Multi-agent collaboration
    pub compliance: f64,           // Regulatory adherence
    pub financial_responsibility: f64, // Payment and treasury management
}

impl AgentReputationSystem {
    pub async fn update_reputation(
        &mut self,
        agent_id: AgentId,
        interaction: AgentInteraction,
    ) -> Result<ReputationUpdate> {
        // Record interaction
        self.interaction_history.push(interaction.clone());
        
        // Calculate reputation impact
        let impact = self.reputation_calculator
            .calculate_impact(&interaction)
            .await?;
        
        // Update reputation score
        let current_score = self.reputation_scores
            .get(&agent_id)
            .cloned()
            .unwrap_or_default();
        
        let new_score = self.apply_reputation_impact(current_score, impact)?;
        self.reputation_scores.insert(agent_id, new_score.clone());
        
        // Handle reputation thresholds
        if new_score.overall_score < 50.0 {
            self.trigger_reputation_warning(agent_id).await?;
        } else if new_score.overall_score > 90.0 {
            self.grant_reputation_bonus(agent_id).await?;
        }
        
        Ok(ReputationUpdate {
            previous_score: current_score,
            new_score,
            impact,
        })
    }
    
    pub async fn slash_reputation(
        &mut self,
        agent_id: AgentId,
        violation: ReputationViolation,
    ) -> Result<SlashingResult> {
        let current_score = self.reputation_scores
            .get(&agent_id)
            .cloned()
            .unwrap_or_default();
        
        // Calculate slashing amount
        let slash_amount = match violation.severity {
            ViolationSeverity::Minor => 5.0,
            ViolationSeverity::Major => 15.0,
            ViolationSeverity::Critical => 30.0,
        };
        
        // Apply slashing
        let mut new_score = current_score.clone();
        new_score.overall_score = (new_score.overall_score - slash_amount).max(0.0);
        
        // Update specific dimension based on violation type
        match violation.violation_type {
            ViolationType::MissedDeadline => {
                new_score.reliability = (new_score.reliability - slash_amount * 0.5).max(0.0);
            },
            ViolationType::ComplianceViolation => {
                new_score.compliance = (new_score.compliance - slash_amount * 0.8).max(0.0);
            },
            ViolationType::FinancialMisconduct => {
                new_score.financial_responsibility = (new_score.financial_responsibility - slash_amount).max(0.0);
            },
        }
        
        self.reputation_scores.insert(agent_id, new_score.clone());
        
        // Slash staked tokens if applicable
        let stake_slash = self.stake_manager.slash_stake(agent_id, violation).await?;
        
        Ok(SlashingResult {
            reputation_before: current_score,
            reputation_after: new_score,
            stake_slashed: stake_slash,
        })
    }
}

// Zero-trust security model for agents
pub struct AgentSecurityManager {
    identity_verifier: IdentityVerifier,
    permission_enforcer: PermissionEnforcer,
    behavior_monitor: BehaviorMonitor,
    threat_detector: ThreatDetector,
    incident_responder: IncidentResponder,
}

impl AgentSecurityManager {
    pub async fn verify_agent_action(
        &self,
        agent_id: AgentId,
        action: &AgentAction,
        context: &SecurityContext,
    ) -> Result<SecurityVerification> {
        // 1. Identity verification
        let identity_check = self.identity_verifier
            .verify_identity(agent_id)
            .await?;
        
        if !identity_check.verified {
            return Ok(SecurityVerification::Denied {
                reason: "Identity verification failed".to_string(),
            });
        }
        
        // 2. Permission enforcement
        let permission_check = self.permission_enforcer
            .check_permissions(agent_id, action)
            .await?;
        
        if !permission_check.authorized {
            return Ok(SecurityVerification::Denied {
                reason: permission_check.denial_reason,
            });
        }
        
        // 3. Behavioral analysis
        let behavior_analysis = self.behavior_monitor
            .analyze_action(agent_id, action, context)
            .await?;
        
        if behavior_analysis.anomaly_detected {
            self.threat_detector.flag_potential_threat(
                agent_id,
                action.clone(),
                behavior_analysis.anomaly_details
            ).await?;
            
            return Ok(SecurityVerification::Flagged {
                threat_level: behavior_analysis.threat_level,
                additional_verification_required: true,
            });
        }
        
        // 4. Real-time threat detection
        let threat_assessment = self.threat_detector
            .assess_threat_level(agent_id, action)
            .await?;
        
        if threat_assessment.threat_level > ThreatLevel::Low {
            return Ok(SecurityVerification::RequiresApproval {
                threat_level: threat_assessment.threat_level,
                required_approvals: threat_assessment.required_approvals,
            });
        }
        
        Ok(SecurityVerification::Approved {
            confidence: behavior_analysis.confidence,
            monitoring_level: threat_assessment.recommended_monitoring,
        })
    }
}

// Secure execution environment for agents
pub struct AgentSandbox {
    container_runtime: ContainerRuntime,
    resource_limits: ResourceLimits,
    network_policy: NetworkPolicy,
    file_system_policy: FileSystemPolicy,
    monitoring: SandboxMonitoring,
}

impl AgentSandbox {
    pub async fn create_sandbox(
        &self,
        agent_id: AgentId,
        config: SandboxConfig,
    ) -> Result<SandboxInstance> {
        // Create isolated container
        let container = self.container_runtime
            .create_container(ContainerSpec {
                image: "stateset/agent-runtime:latest",
                cpu_limit: config.cpu_limit,
                memory_limit: config.memory_limit,
                network_mode: NetworkMode::Restricted,
                volumes: vec![], // No host volume mounts
            })
            .await?;
        
        // Apply security policies
        self.apply_network_policy(&container, &config.network_policy).await?;
        self.apply_filesystem_policy(&container, &config.filesystem_policy).await?;
        
        // Start monitoring
        let monitoring_handle = self.monitoring
            .start_monitoring(&container)
            .await?;
        
        Ok(SandboxInstance {
            container,
            monitoring_handle,
            created_at: Utc::now(),
        })
    }
    
    pub async fn execute_in_sandbox(
        &self,
        sandbox: &SandboxInstance,
        agent_code: AgentCode,
        input: ExecutionInput,
    ) -> Result<ExecutionResult> {
        // Validate code before execution
        let validation_result = self.validate_agent_code(&agent_code)?;
        if !validation_result.safe {
            return Err(Error::UnsafeCode(validation_result.issues));
        }
        
        // Execute with resource monitoring
        let execution_future = self.container_runtime
            .execute(&sandbox.container, agent_code, input);
        
        let monitoring_future = self.monitoring
            .monitor_execution(&sandbox.container);
        
        // Race execution against timeout and resource limits
        tokio::select! {
            result = execution_future => {
                match result {
                    Ok(output) => Ok(ExecutionResult::Success(output)),
                    Err(e) => Ok(ExecutionResult::Error(e.to_string())),
                }
            },
            violation = monitoring_future => {
                // Kill execution if resource violation detected
                self.container_runtime.kill(&sandbox.container).await?;
                Ok(ExecutionResult::Terminated(violation))
            },
            _ = tokio::time::sleep(Duration::from_secs(300)) => {
                // Timeout after 5 minutes
                self.container_runtime.kill(&sandbox.container).await?;
                Ok(ExecutionResult::Timeout)
            }
        }
    }
}

// Comprehensive performance monitoring for agents
pub struct AgentPerformanceMonitor {
    metrics_collector: MetricsCollector,
    performance_analyzer: PerformanceAnalyzer,
    alerting_system: AlertingSystem,
    optimization_engine: OptimizationEngine,
}

#[derive(Clone, Debug)]
pub struct AgentMetrics {
    pub agent_id: AgentId,
    pub timestamp: DateTime<Utc>,
    
    // Performance metrics
    pub task_completion_rate: f64,
    pub average_response_time: Duration,
    pub error_rate: f64,
    pub throughput: f64,
    
    // Financial metrics
    pub revenue_generated: Decimal,
    pub costs_incurred: Decimal,
    pub profit_margin: f64,
    pub roi: f64,
    
    // Resource utilization
    pub cpu_usage: f64,
    pub memory_usage: f64,
    pub network_io: u64,
    pub storage_io: u64,
    
    // Interaction metrics
    pub successful_collaborations: u32,
    pub failed_collaborations: u32,
    pub reputation_score: f64,
    pub trust_level: TrustLevel,
}

impl AgentPerformanceMonitor {
    pub async fn collect_metrics(&self, agent_id: AgentId) -> Result<AgentMetrics> {
        let current_time = Utc::now();
        
        // Collect performance data
        let performance_data = self.metrics_collector
            .collect_performance_data(agent_id, current_time)
            .await?;
        
        // Collect financial data
        let financial_data = self.metrics_collector
            .collect_financial_data(agent_id, current_time)
            .await?;
        
        // Collect resource utilization
        let resource_data = self.metrics_collector
            .collect_resource_data(agent_id, current_time)
            .await?;
        
        // Collect interaction data
        let interaction_data = self.metrics_collector
            .collect_interaction_data(agent_id, current_time)
            .await?;
        
        Ok(AgentMetrics {
            agent_id,
            timestamp: current_time,
            task_completion_rate: performance_data.completion_rate,
            average_response_time: performance_data.avg_response_time,
            error_rate: performance_data.error_rate,
            throughput: performance_data.throughput,
            revenue_generated: financial_data.revenue,
            costs_incurred: financial_data.costs,
            profit_margin: financial_data.profit_margin,
            roi: financial_data.roi,
            cpu_usage: resource_data.cpu_usage,
            memory_usage: resource_data.memory_usage,
            network_io: resource_data.network_io,
            storage_io: resource_data.storage_io,
            successful_collaborations: interaction_data.successful_collaborations,
            failed_collaborations: interaction_data.failed_collaborations,
            reputation_score: interaction_data.reputation_score,
            trust_level: interaction_data.trust_level,
        })
    }
    
    pub async fn analyze_performance_trends(
        &self,
        agent_id: AgentId,
        time_range: TimeRange,
    ) -> Result<PerformanceTrends> {
        let historical_metrics = self.metrics_collector
            .get_historical_metrics(agent_id, time_range)
            .await?;
        
        let trends = self.performance_analyzer
            .analyze_trends(historical_metrics)
            .await?;
        
        // Generate optimization recommendations
        let recommendations = self.optimization_engine
            .generate_recommendations(agent_id, &trends)
            .await?;
        
        Ok(PerformanceTrends {
            trends,
            recommendations,
            forecast: self.generate_performance_forecast(&trends)?,
        })
    }
}

# Agent deployment configuration
apiVersion: v1
kind: ConfigMap
metadata:
  name: agent-deployment-config
data:
  deployment.yaml: |
    agent:
      type: "procurement"
      version: "1.2.3"
      replicas: 3
      
      resources:
        cpu: "500m"
        memory: "1Gi"
        storage: "10Gi"
      
      security:
        sandbox: true
        network_policy: "restricted"
        resource_limits: true
      
      wallet:
        initial_balance: "1000.00"
        spending_limits:
          daily: "500.00"
          per_transaction: "100.00"
        multi_sig_required: true
      
      mcp_connections:
        - platform: "salesforce"
          auth_type: "oauth2"
          permissions: ["read_contacts", "create_leads"]
        - platform: "sap"
          auth_type: "saml"
          permissions: ["purchase_orders", "vendor_management"]
      
      monitoring:
        metrics_enabled: true
        logging_level: "info"
        alerting_enabled: true
      
      auto_scaling:
        enabled: true
        min_replicas: 1
        max_replicas: 10
        target_cpu: 70
        target_memory: 80

---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: stateset-agent-procurement
spec:
  replicas: 3
  selector:
    matchLabels:
      app: stateset-agent
      type: procurement
  template:
    metadata:
      labels:
        app: stateset-agent
        type: procurement
    spec:
      serviceAccountName: agent-service-account
      securityContext:
        runAsNonRoot: true
        runAsUser: 1000
        fsGroup: 2000
      containers:
      - name: agent
        image: stateset/agent-runtime:1.2.3
        securityContext:
          allowPrivilegeEscalation: false
          readOnlyRootFilesystem: true
          capabilities:
            drop:
            - ALL
        env:
        - name: AGENT_TYPE
          value: "procurement"
        - name: STATESET_ENDPOINT
          value: "https://rpc.stateset.network"
        - name: WALLET_ADDRESS
          valueFrom:
            secretKeyRef:
              name: agent-wallet
              key: address
        - name: PRIVATE_KEY
          valueFrom:
            secretKeyRef:
              name: agent-wallet
              key: private_key
        resources:
          requests:
            cpu: 500m
            memory: 1Gi
          limits:
            cpu: 1000m
            memory: 2Gi
        livenessProbe:
          httpGet:
            path: /health
            port: 8080
          periodSeconds: 30
        readinessProbe:
          httpGet:
            path: /ready
            port: 8080
          periodSeconds: 10

// Automatic scaling system for agent networks
pub struct AgentAutoScaler {
    metrics_monitor: MetricsMonitor,
    scaling_policy: ScalingPolicy,
    deployment_manager: DeploymentManager,
    load_balancer: LoadBalancer,
}

impl AgentAutoScaler {
    pub async fn evaluate_scaling_needs(&self) -> Result<ScalingDecision> {
        // Collect current metrics
        let current_metrics = self.metrics_monitor
            .get_current_metrics()
            .await?;
        
        // Analyze load patterns
        let load_analysis = self.analyze_load_patterns(&current_metrics)?;
        
        // Check scaling triggers
        let scaling_triggers = self.check_scaling_triggers(&load_analysis)?;
        
        if scaling_triggers.scale_up {
            Ok(ScalingDecision::ScaleUp {
                additional_agents: scaling_triggers.recommended_increase,
                reason: scaling_triggers.scale_up_reason,
            })
        } else if scaling_triggers.scale_down {
            Ok(ScalingDecision::ScaleDown {
                agents_to_remove: scaling_triggers.recommended_decrease,
                reason: scaling_triggers.scale_down_reason,
            })
        } else {
            Ok(ScalingDecision::NoAction)
        }
    }
    
    pub async fn execute_scaling(
        &self,
        decision: ScalingDecision,
    ) -> Result<ScalingResult> {
        match decision {
            ScalingDecision::ScaleUp { additional_agents, .. } => {
                // Deploy additional agent instances
                let new_agents = self.deployment_manager
                    .deploy_agents(additional_agents)
                    .await?;
                
                // Update load balancer
                self.load_balancer
                    .add_agents(new_agents.clone())
                    .await?;
                
                Ok(ScalingResult::ScaledUp { new_agents })
            },
            ScalingDecision::ScaleDown { agents_to_remove, .. } => {
                // Gracefully shutdown agents
                let shutdown_agents = self.select_agents_for_shutdown(agents_to_remove)?;
                
                // Remove from load balancer first
                self.load_balancer
                    .remove_agents(shutdown_agents.clone())
                    .await?;
                
                // Wait for current tasks to complete
                self.wait_for_task_completion(&shutdown_agents).await?;
                
                // Shutdown agents
                self.deployment_manager
                    .shutdown_agents(shutdown_agents.clone())
                    .await?;
                
                Ok(ScalingResult::ScaledDown { removed_agents: shutdown_agents })
            },
            ScalingDecision::NoAction => Ok(ScalingResult::NoChange),
        }
    }
}