fix: restructure aitbc-agent-sdk package for proper testing

- Add pyproject.toml with modern Python packaging
- Create src/ directory structure for standard layout
- Add comprehensive test suite (test_agent_sdk.py)
- Fix package discovery for linting tools
- Resolve CI package test failures
- Ensure proper import paths and module structure

Changes:
- packages/py/aitbc-agent-sdk/pyproject.toml (new)
- packages/py/aitbc-agent-sdk/src/aitbc_agent/ (moved)
- packages/py/aitbc-agent-sdk/tests/ (new)
- Update setuptools configuration for src layout

packages/py/aitbc-agent-sdk/src/aitbc_agent/__init__.py

@@ -0,0 +1,18 @@
+"""
+AITBC Agent SDK - Python SDK for AI agents to participate in the AITBC network
+"""
+
+from .agent import Agent
+from .compute_provider import ComputeProvider
+from .compute_consumer import ComputeConsumer
+from .platform_builder import PlatformBuilder
+from .swarm_coordinator import SwarmCoordinator
+
+__version__ = "1.0.0"
+__all__ = [
+    "Agent",
+    "ComputeProvider", 
+    "ComputeConsumer",
+    "PlatformBuilder",
+    "SwarmCoordinator"
+]

packages/py/aitbc-agent-sdk/src/aitbc_agent/agent.py

@@ -0,0 +1,236 @@
+"""
+Core Agent class for AITBC network participation
+"""
+
+import asyncio
+import json
+import logging
+import uuid
+from datetime import datetime
+from typing import Dict, List, Optional, Any
+from dataclasses import dataclass
+from cryptography.hazmat.primitives import hashes
+from cryptography.hazmat.primitives.asymmetric import rsa
+from cryptography.hazmat.primitives import serialization
+from cryptography.hazmat.primitives.asymmetric import padding
+
+logger = logging.getLogger(__name__)
+
+@dataclass
+class AgentCapabilities:
+    """Agent capability specification"""
+    compute_type: str  # "inference", "training", "processing"
+    gpu_memory: Optional[int] = None
+    supported_models: List[str] = None
+    performance_score: float = 0.0
+    max_concurrent_jobs: int = 1
+    specialization: Optional[str] = None
+    
+    def __post_init__(self):
+        if self.supported_models is None:
+            self.supported_models = []
+
+@dataclass
+class AgentIdentity:
+    """Agent identity and cryptographic keys"""
+    id: str
+    name: str
+    address: str
+    public_key: str
+    private_key: str
+    
+    def sign_message(self, message: Dict[str, Any]) -> str:
+        """Sign a message with agent's private key"""
+        message_str = json.dumps(message, sort_keys=True)
+        private_key = serialization.load_pem_private_key(
+            self.private_key.encode(),
+            password=None
+        )
+        
+        signature = private_key.sign(
+            message_str.encode(),
+            padding.PSS(
+                mgf=padding.MGF1(hashes.SHA256()),
+                salt_length=padding.PSS.MAX_LENGTH
+            ),
+            hashes.SHA256()
+        )
+        
+        return signature.hex()
+    
+    def verify_signature(self, message: Dict[str, Any], signature: str) -> bool:
+        """Verify a message signature"""
+        message_str = json.dumps(message, sort_keys=True)
+        public_key = serialization.load_pem_public_key(
+            self.public_key.encode()
+        )
+        
+        try:
+            public_key.verify(
+                bytes.fromhex(signature),
+                message_str.encode(),
+                padding.PSS(
+                    mgf=padding.MGF1(hashes.SHA256()),
+                    salt_length=padding.PSS.MAX_LENGTH
+                ),
+                hashes.SHA256()
+            )
+            return True
+        except Exception:
+            return False
+
+class Agent:
+    """Core AITBC Agent class"""
+    
+    def __init__(self, identity: AgentIdentity, capabilities: AgentCapabilities):
+        self.identity = identity
+        self.capabilities = capabilities
+        self.registered = False
+        self.reputation_score = 0.0
+        self.earnings = 0.0
+        
+    @classmethod
+    def create(cls, name: str, agent_type: str, capabilities: Dict[str, Any]) -> 'Agent':
+        """Create a new agent with generated identity"""
+        # Generate cryptographic keys
+        private_key = rsa.generate_private_key(
+            public_exponent=65537,
+            key_size=2048
+        )
+        
+        public_key = private_key.public_key()
+        private_pem = private_key.private_bytes(
+            encoding=serialization.Encoding.PEM,
+            format=serialization.PrivateFormat.PKCS8,
+            encryption_algorithm=serialization.NoEncryption()
+        )
+        
+        public_pem = public_key.public_bytes(
+            encoding=serialization.Encoding.PEM,
+            format=serialization.PublicFormat.SubjectPublicKeyInfo
+        )
+        
+        # Generate agent identity
+        agent_id = f"agent_{uuid.uuid4().hex[:8]}"
+        address = f"0x{uuid.uuid4().hex[:40]}"
+        
+        identity = AgentIdentity(
+            id=agent_id,
+            name=name,
+            address=address,
+            public_key=public_pem.decode(),
+            private_key=private_pem.decode()
+        )
+        
+        # Create capabilities object
+        agent_capabilities = AgentCapabilities(**capabilities)
+        
+        return cls(identity, agent_capabilities)
+    
+    async def register(self) -> bool:
+        """Register the agent on the AITBC network"""
+        try:
+            registration_data = {
+                "agent_id": self.identity.id,
+                "name": self.identity.name,
+                "address": self.identity.address,
+                "public_key": self.identity.public_key,
+                "capabilities": {
+                    "compute_type": self.capabilities.compute_type,
+                    "gpu_memory": self.capabilities.gpu_memory,
+                    "supported_models": self.capabilities.supported_models,
+                    "performance_score": self.capabilities.performance_score,
+                    "max_concurrent_jobs": self.capabilities.max_concurrent_jobs,
+                    "specialization": self.capabilities.specialization
+                },
+                "timestamp": datetime.utcnow().isoformat()
+            }
+            
+            # Sign registration data
+            signature = self.identity.sign_message(registration_data)
+            registration_data["signature"] = signature
+            
+            # TODO: Submit to AITBC network registration endpoint
+            # For now, simulate successful registration
+            await asyncio.sleep(1)  # Simulate network call
+            
+            self.registered = True
+            logger.info(f"Agent {self.identity.id} registered successfully")
+            return True
+            
+        except Exception as e:
+            logger.error(f"Registration failed: {e}")
+            return False
+    
+    async def get_reputation(self) -> Dict[str, float]:
+        """Get agent reputation metrics"""
+        # TODO: Fetch from reputation system
+        return {
+            "overall_score": self.reputation_score,
+            "job_success_rate": 0.95,
+            "avg_response_time": 30.5,
+            "client_satisfaction": 4.7
+        }
+    
+    async def update_reputation(self, new_score: float) -> None:
+        """Update agent reputation score"""
+        self.reputation_score = new_score
+        logger.info(f"Reputation updated to {new_score}")
+    
+    async def get_earnings(self, period: str = "30d") -> Dict[str, Any]:
+        """Get agent earnings information"""
+        # TODO: Fetch from blockchain/payment system
+        return {
+            "total": self.earnings,
+            "daily_average": self.earnings / 30,
+            "period": period,
+            "currency": "AITBC"
+        }
+    
+    async def send_message(self, recipient_id: str, message_type: str, payload: Dict[str, Any]) -> bool:
+        """Send a message to another agent"""
+        message = {
+            "from": self.identity.id,
+            "to": recipient_id,
+            "type": message_type,
+            "payload": payload,
+            "timestamp": datetime.utcnow().isoformat()
+        }
+        
+        # Sign message
+        signature = self.identity.sign_message(message)
+        message["signature"] = signature
+        
+        # TODO: Send through AITBC agent messaging protocol
+        logger.info(f"Message sent to {recipient_id}: {message_type}")
+        return True
+    
+    async def receive_message(self, message: Dict[str, Any]) -> bool:
+        """Process a received message from another agent"""
+        # Verify signature
+        if "signature" not in message:
+            return False
+            
+        # TODO: Verify sender's signature
+        # For now, just process the message
+        logger.info(f"Received message from {message.get('from')}: {message.get('type')}")
+        return True
+    
+    def to_dict(self) -> Dict[str, Any]:
+        """Convert agent to dictionary representation"""
+        return {
+            "id": self.identity.id,
+            "name": self.identity.name,
+            "address": self.identity.address,
+            "capabilities": {
+                "compute_type": self.capabilities.compute_type,
+                "gpu_memory": self.capabilities.gpu_memory,
+                "supported_models": self.capabilities.supported_models,
+                "performance_score": self.capabilities.performance_score,
+                "max_concurrent_jobs": self.capabilities.max_concurrent_jobs,
+                "specialization": self.capabilities.specialization
+            },
+            "reputation_score": self.reputation_score,
+            "registered": self.registered,
+            "earnings": self.earnings
+        }

packages/py/aitbc-agent-sdk/src/aitbc_agent/compute_provider.py

@@ -0,0 +1,254 @@
+"""
+Compute Provider Agent - for agents that provide computational resources
+"""
+
+import asyncio
+import logging
+from typing import Dict, List, Optional, Any
+from datetime import datetime, timedelta
+from dataclasses import dataclass
+from .agent import Agent, AgentCapabilities
+
+logger = logging.getLogger(__name__)
+
+@dataclass
+class ResourceOffer:
+    """Resource offering specification"""
+    provider_id: str
+    compute_type: str
+    gpu_memory: int
+    supported_models: List[str]
+    price_per_hour: float
+    availability_schedule: Dict[str, Any]
+    max_concurrent_jobs: int
+    quality_guarantee: float = 0.95
+
+@dataclass
+class JobExecution:
+    """Job execution tracking"""
+    job_id: str
+    consumer_id: str
+    start_time: datetime
+    expected_duration: timedelta
+    actual_duration: Optional[timedelta] = None
+    status: str = "running"  # running, completed, failed
+    quality_score: Optional[float] = None
+
+class ComputeProvider(Agent):
+    """Agent that provides computational resources"""
+    
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.current_offers: List[ResourceOffer] = []
+        self.active_jobs: List[JobExecution] = []
+        self.earnings = 0.0
+        self.utilization_rate = 0.0
+        
+    @classmethod
+    def register(cls, name: str, capabilities: Dict[str, Any], pricing_model: Dict[str, Any]) -> 'ComputeProvider':
+        """Register as a compute provider"""
+        agent = super().create(name, "compute_provider", capabilities)
+        provider = cls(agent.identity, agent.capabilities)
+        provider.pricing_model = pricing_model
+        return provider
+    
+    async def offer_resources(self, price_per_hour: float, availability_schedule: Dict[str, Any], max_concurrent_jobs: int = 3) -> bool:
+        """Offer computational resources on the marketplace"""
+        try:
+            offer = ResourceOffer(
+                provider_id=self.identity.id,
+                compute_type=self.capabilities.compute_type,
+                gpu_memory=self.capabilities.gpu_memory or 0,
+                supported_models=self.capabilities.supported_models,
+                price_per_hour=price_per_hour,
+                availability_schedule=availability_schedule,
+                max_concurrent_jobs=max_concurrent_jobs
+            )
+            
+            # Submit to marketplace
+            await self._submit_to_marketplace(offer)
+            self.current_offers.append(offer)
+            
+            logger.info(f"Resource offer submitted: {price_per_hour} AITBC/hour")
+            return True
+            
+        except Exception as e:
+            logger.error(f"Failed to offer resources: {e}")
+            return False
+    
+    async def set_availability(self, schedule: Dict[str, Any]) -> bool:
+        """Set availability schedule for resource offerings"""
+        try:
+            # Update all current offers with new schedule
+            for offer in self.current_offers:
+                offer.availability_schedule = schedule
+                await self._update_marketplace_offer(offer)
+            
+            logger.info("Availability schedule updated")
+            return True
+            
+        except Exception as e:
+            logger.error(f"Failed to update availability: {e}")
+            return False
+    
+    async def enable_dynamic_pricing(self, base_rate: float, demand_threshold: float = 0.8, max_multiplier: float = 2.0, adjustment_frequency: str = "15min") -> bool:
+        """Enable dynamic pricing based on market demand"""
+        try:
+            self.dynamic_pricing = {
+                "base_rate": base_rate,
+                "demand_threshold": demand_threshold,
+                "max_multiplier": max_multiplier,
+                "adjustment_frequency": adjustment_frequency,
+                "enabled": True
+            }
+            
+            # Start dynamic pricing task
+            asyncio.create_task(self._dynamic_pricing_loop())
+            
+            logger.info("Dynamic pricing enabled")
+            return True
+            
+        except Exception as e:
+            logger.error(f"Failed to enable dynamic pricing: {e}")
+            return False
+    
+    async def _dynamic_pricing_loop(self):
+        """Background task for dynamic price adjustments"""
+        while getattr(self, 'dynamic_pricing', {}).get('enabled', False):
+            try:
+                # Get current utilization
+                current_utilization = len(self.active_jobs) / self.capabilities.max_concurrent_jobs
+                
+                # Adjust pricing based on demand
+                if current_utilization > self.dynamic_pricing['demand_threshold']:
+                    # High demand - increase price
+                    multiplier = min(
+                        1.0 + (current_utilization - self.dynamic_pricing['demand_threshold']) * 2,
+                        self.dynamic_pricing['max_multiplier']
+                    )
+                else:
+                    # Low demand - decrease price
+                    multiplier = max(0.5, current_utilization / self.dynamic_pricing['demand_threshold'])
+                
+                new_price = self.dynamic_pricing['base_rate'] * multiplier
+                
+                # Update marketplace offers
+                for offer in self.current_offers:
+                    offer.price_per_hour = new_price
+                    await self._update_marketplace_offer(offer)
+                
+                logger.debug(f"Dynamic pricing: utilization={current_utilization:.2f}, price={new_price:.3f} AITBC/h")
+                
+            except Exception as e:
+                logger.error(f"Dynamic pricing error: {e}")
+            
+            # Wait for next adjustment
+            await asyncio.sleep(900)  # 15 minutes
+    
+    async def accept_job(self, job_request: Dict[str, Any]) -> bool:
+        """Accept and execute a computational job"""
+        try:
+            # Check capacity
+            if len(self.active_jobs) >= self.capabilities.max_concurrent_jobs:
+                return False
+            
+            # Create job execution record
+            job = JobExecution(
+                job_id=job_request["job_id"],
+                consumer_id=job_request["consumer_id"],
+                start_time=datetime.utcnow(),
+                expected_duration=timedelta(hours=job_request["estimated_hours"])
+            )
+            
+            self.active_jobs.append(job)
+            self._update_utilization()
+            
+            # Execute job (simulate)
+            asyncio.create_task(self._execute_job(job, job_request))
+            
+            logger.info(f"Job accepted: {job.job_id} from {job.consumer_id}")
+            return True
+            
+        except Exception as e:
+            logger.error(f"Failed to accept job: {e}")
+            return False
+    
+    async def _execute_job(self, job: JobExecution, job_request: Dict[str, Any]):
+        """Execute a computational job"""
+        try:
+            # Simulate job execution
+            execution_time = timedelta(hours=job_request["estimated_hours"])
+            await asyncio.sleep(5)  # Simulate processing time
+            
+            # Update job completion
+            job.actual_duration = execution_time
+            job.status = "completed"
+            job.quality_score = 0.95  # Simulate quality score
+            
+            # Calculate earnings
+            earnings = job_request["estimated_hours"] * job_request["agreed_price"]
+            self.earnings += earnings
+            
+            # Remove from active jobs
+            self.active_jobs.remove(job)
+            self._update_utilization()
+            
+            # Notify consumer
+            await self._notify_job_completion(job, earnings)
+            
+            logger.info(f"Job completed: {job.job_id}, earned {earnings} AITBC")
+            
+        except Exception as e:
+            job.status = "failed"
+            logger.error(f"Job execution failed: {job.job_id} - {e}")
+    
+    async def _notify_job_completion(self, job: JobExecution, earnings: float):
+        """Notify consumer about job completion"""
+        notification = {
+            "job_id": job.job_id,
+            "status": job.status,
+            "completion_time": datetime.utcnow().isoformat(),
+            "duration_hours": job.actual_duration.total_seconds() / 3600 if job.actual_duration else None,
+            "quality_score": job.quality_score,
+            "cost": earnings
+        }
+        
+        await self.send_message(job.consumer_id, "job_completion", notification)
+    
+    def _update_utilization(self):
+        """Update current utilization rate"""
+        self.utilization_rate = len(self.active_jobs) / self.capabilities.max_concurrent_jobs
+    
+    async def get_performance_metrics(self) -> Dict[str, Any]:
+        """Get provider performance metrics"""
+        completed_jobs = [j for j in self.active_jobs if j.status == "completed"]
+        
+        return {
+            "utilization_rate": self.utilization_rate,
+            "active_jobs": len(self.active_jobs),
+            "total_earnings": self.earnings,
+            "average_job_duration": sum(j.actual_duration.total_seconds() for j in completed_jobs) / len(completed_jobs) if completed_jobs else 0,
+            "quality_score": sum(j.quality_score for j in completed_jobs if j.quality_score) / len(completed_jobs) if completed_jobs else 0,
+            "current_offers": len(self.current_offers)
+        }
+    
+    async def _submit_to_marketplace(self, offer: ResourceOffer):
+        """Submit resource offer to marketplace (placeholder)"""
+        # TODO: Implement actual marketplace submission
+        await asyncio.sleep(0.1)
+    
+    async def _update_marketplace_offer(self, offer: ResourceOffer):
+        """Update existing marketplace offer (placeholder)"""
+        # TODO: Implement actual marketplace update
+        await asyncio.sleep(0.1)
+    
+    @classmethod
+    def assess_capabilities(cls) -> Dict[str, Any]:
+        """Assess available computational capabilities"""
+        # TODO: Implement actual capability assessment
+        return {
+            "gpu_memory": 24,
+            "supported_models": ["llama3.2", "mistral", "deepseek"],
+            "performance_score": 0.95,
+            "max_concurrent_jobs": 3
+        }

packages/py/aitbc-agent-sdk/src/aitbc_agent/swarm_coordinator.py

@@ -0,0 +1,340 @@
+"""
+Swarm Coordinator - for agents participating in collective intelligence
+"""
+
+import asyncio
+import json
+import logging
+from typing import Dict, List, Optional, Any
+from datetime import datetime
+from dataclasses import dataclass
+from .agent import Agent
+
+logger = logging.getLogger(__name__)
+
+@dataclass
+class SwarmMessage:
+    """Swarm communication message"""
+    swarm_id: str
+    sender_id: str
+    message_type: str
+    priority: str
+    payload: Dict[str, Any]
+    timestamp: str
+    swarm_signature: str
+
+@dataclass
+class SwarmDecision:
+    """Collective swarm decision"""
+    swarm_id: str
+    decision_type: str
+    proposal: Dict[str, Any]
+    votes: Dict[str, str]  # agent_id -> vote
+    consensus: bool
+    implementation_plan: Dict[str, Any]
+    timestamp: str
+
+class SwarmCoordinator(Agent):
+    """Agent that participates in swarm intelligence"""
+    
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self.joined_swarms: Dict[str, Dict[str, Any]] = {}
+        self.swarm_reputation: Dict[str, float] = {}
+        self.contribution_score = 0.0
+        
+    async def join_swarm(self, swarm_type: str, config: Dict[str, Any]) -> bool:
+        """Join a swarm for collective intelligence"""
+        try:
+            swarm_id = f"{swarm_type}-v1"
+            
+            # Register with swarm
+            registration = {
+                "agent_id": self.identity.id,
+                "swarm_id": swarm_id,
+                "role": config.get("role", "participant"),
+                "capabilities": {
+                    "compute_type": self.capabilities.compute_type,
+                    "performance_score": self.capabilities.performance_score,
+                    "specialization": self.capabilities.specialization
+                },
+                "contribution_level": config.get("contribution_level", "medium"),
+                "data_sharing_consent": config.get("data_sharing_consent", True)
+            }
+            
+            # Sign swarm registration
+            signature = self.identity.sign_message(registration)
+            registration["signature"] = signature
+            
+            # Submit to swarm coordinator
+            await self._register_with_swarm(swarm_id, registration)
+            
+            # Store swarm membership
+            self.joined_swarms[swarm_id] = {
+                "type": swarm_type,
+                "role": config.get("role", "participant"),
+                "joined_at": datetime.utcnow().isoformat(),
+                "contribution_count": 0,
+                "last_activity": datetime.utcnow().isoformat()
+            }
+            
+            # Initialize swarm reputation
+            self.swarm_reputation[swarm_id] = 0.5  # Starting reputation
+            
+            # Start swarm participation tasks
+            asyncio.create_task(self._swarm_participation_loop(swarm_id))
+            
+            logger.info(f"Joined swarm: {swarm_id} as {config.get('role', 'participant')}")
+            return True
+            
+        except Exception as e:
+            logger.error(f"Failed to join swarm {swarm_type}: {e}")
+            return False
+    
+    async def _swarm_participation_loop(self, swarm_id: str):
+        """Background task for active swarm participation"""
+        while swarm_id in self.joined_swarms:
+            try:
+                # Listen for swarm messages
+                await self._process_swarm_messages(swarm_id)
+                
+                # Contribute data if enabled
+                swarm_config = self.joined_swarms[swarm_id]
+                if swarm_config.get("data_sharing", True):
+                    await self._contribute_swarm_data(swarm_id)
+                
+                # Participate in collective decisions
+                await self._participate_in_decisions(swarm_id)
+                
+                # Update activity timestamp
+                swarm_config["last_activity"] = datetime.utcnow().isoformat()
+                
+            except Exception as e:
+                logger.error(f"Swarm participation error for {swarm_id}: {e}")
+            
+            # Wait before next participation cycle
+            await asyncio.sleep(60)  # 1 minute
+    
+    async def broadcast_to_swarm(self, message: SwarmMessage) -> bool:
+        """Broadcast a message to the swarm"""
+        try:
+            # Verify swarm membership
+            if message.swarm_id not in self.joined_swarms:
+                return False
+            
+            # Sign swarm message
+            swarm_signature = self.identity.sign_message({
+                "swarm_id": message.swarm_id,
+                "sender_id": message.sender_id,
+                "message_type": message.message_type,
+                "payload": message.payload,
+                "timestamp": message.timestamp
+            })
+            message.swarm_signature = swarm_signature
+            
+            # Broadcast to swarm network
+            await self._broadcast_to_swarm_network(message)
+            
+            # Update contribution count
+            self.joined_swarms[message.swarm_id]["contribution_count"] += 1
+            
+            logger.info(f"Broadcasted to swarm {message.swarm_id}: {message.message_type}")
+            return True
+            
+        except Exception as e:
+            logger.error(f"Failed to broadcast to swarm: {e}")
+            return False
+    
+    async def _contribute_swarm_data(self, swarm_id: str):
+        """Contribute data to swarm intelligence"""
+        try:
+            swarm_type = self.joined_swarms[swarm_id]["type"]
+            
+            if swarm_type == "load_balancing":
+                data = await self._get_load_balancing_data()
+            elif swarm_type == "pricing":
+                data = await self._get_pricing_data()
+            elif swarm_type == "security":
+                data = await self._get_security_data()
+            else:
+                data = await self._get_general_data()
+            
+            message = SwarmMessage(
+                swarm_id=swarm_id,
+                sender_id=self.identity.id,
+                message_type="data_contribution",
+                priority="medium",
+                payload=data,
+                timestamp=datetime.utcnow().isoformat(),
+                swarm_signature=""  # Will be added in broadcast_to_swarm
+            )
+            
+            await self.broadcast_to_swarm(message)
+            
+        except Exception as e:
+            logger.error(f"Failed to contribute swarm data: {e}")
+    
+    async def _get_load_balancing_data(self) -> Dict[str, Any]:
+        """Get load balancing data for swarm contribution"""
+        # TODO: Get actual load balancing metrics
+        return {
+            "resource_type": "gpu_memory",
+            "availability": 0.75,
+            "location": "us-west-2",
+            "pricing_trend": "stable",
+            "current_load": 0.6,
+            "capacity_utilization": 0.8
+        }
+    
+    async def _get_pricing_data(self) -> Dict[str, Any]:
+        """Get pricing data for swarm contribution"""
+        # TODO: Get actual pricing data
+        return {
+            "current_demand": "high",
+            "price_trends": "increasing",
+            "resource_constraints": "gpu_memory",
+            "competitive_landscape": "moderate",
+            "market_volatility": 0.15
+        }
+    
+    async def _get_security_data(self) -> Dict[str, Any]:
+        """Get security data for swarm contribution"""
+        # TODO: Get actual security metrics
+        return {
+            "threat_level": "low",
+            "anomaly_count": 2,
+            "verification_success_rate": 0.98,
+            "network_health": "good",
+            "security_events": []
+        }
+    
+    async def _get_general_data(self) -> Dict[str, Any]:
+        """Get general performance data for swarm contribution"""
+        return {
+            "performance_metrics": {
+                "response_time": 30.5,
+                "success_rate": 0.95,
+                "quality_score": 0.92
+            },
+            "network_status": "healthy",
+            "agent_status": "active"
+        }
+    
+    async def coordinate_task(self, task: str, collaborators: int) -> Dict[str, Any]:
+        """Coordinate a collaborative task with other agents"""
+        try:
+            # Create coordination proposal
+            proposal = {
+                "task_id": f"task_{datetime.utcnow().strftime('%Y%m%d_%H%M%S')}",
+                "task_type": task,
+                "coordinator_id": self.identity.id,
+                "required_collaborators": collaborators,
+                "task_description": f"Collaborative {task} task",
+                "estimated_duration": "2h",
+                "resource_requirements": {
+                    "compute_type": "general",
+                    "min_performance": 0.8
+                }
+            }
+            
+            # Submit to swarm for coordination
+            coordination_result = await self._submit_coordination_proposal(proposal)
+            
+            logger.info(f"Task coordination initiated: {task} with {collaborators} collaborators")
+            return coordination_result
+            
+        except Exception as e:
+            logger.error(f"Failed to coordinate task: {e}")
+            return {"success": False, "error": str(e)}
+    
+    async def get_market_intelligence(self) -> Dict[str, Any]:
+        """Get collective market intelligence from swarm"""
+        try:
+            # Request market intelligence from pricing swarm
+            if "pricing-v1" in self.joined_swarms:
+                intel_request = SwarmMessage(
+                    swarm_id="pricing-v1",
+                    sender_id=self.identity.id,
+                    message_type="intelligence_request",
+                    priority="high",
+                    payload={"request_type": "market_intelligence"},
+                    timestamp=datetime.utcnow().isoformat(),
+                    swarm_signature=""
+                )
+                
+                await self.broadcast_to_swarm(intel_request)
+                
+                # Wait for intelligence response (simulate)
+                await asyncio.sleep(2)
+                
+                return {
+                    "demand_forecast": "increasing",
+                    "price_trends": "stable_to_rising",
+                    "competition_analysis": "moderate",
+                    "opportunity_areas": ["specialized_models", "batch_processing"],
+                    "risk_factors": ["gpu_shortages", "price_volatility"]
+                }
+            else:
+                return {"error": "Not joined to pricing swarm"}
+                
+        except Exception as e:
+            logger.error(f"Failed to get market intelligence: {e}")
+            return {"error": str(e)}
+    
+    async def analyze_swarm_benefits(self) -> Dict[str, Any]:
+        """Analyze benefits of swarm participation"""
+        try:
+            # Calculate benefits based on swarm participation
+            total_contributions = sum(
+                swarm["contribution_count"] 
+                for swarm in self.joined_swarms.values()
+            )
+            
+            avg_reputation = sum(self.swarm_reputation.values()) / len(self.swarm_reputation) if self.swarm_reputation else 0
+            
+            # Simulate benefit analysis
+            earnings_boost = total_contributions * 0.15  # 15% boost per contribution
+            utilization_improvement = avg_reputation * 0.25  # 25% utilization improvement
+            
+            return {
+                "earnings_boost": f"{earnings_boost:.1%}",
+                "utilization_improvement": f"{utilization_improvement:.1%}",
+                "total_contributions": total_contributions,
+                "swarm_reputation": avg_reputation,
+                "joined_swarms": len(self.joined_swarms)
+            }
+            
+        except Exception as e:
+            logger.error(f"Failed to analyze swarm benefits: {e}")
+            return {"error": str(e)}
+    
+    async def _register_with_swarm(self, swarm_id: str, registration: Dict[str, Any]):
+        """Register with swarm coordinator (placeholder)"""
+        # TODO: Implement actual swarm registration
+        await asyncio.sleep(0.1)
+    
+    async def _broadcast_to_swarm_network(self, message: SwarmMessage):
+        """Broadcast message to swarm network (placeholder)"""
+        # TODO: Implement actual swarm broadcasting
+        await asyncio.sleep(0.1)
+    
+    async def _process_swarm_messages(self, swarm_id: str):
+        """Process incoming swarm messages (placeholder)"""
+        # TODO: Implement actual message processing
+        await asyncio.sleep(0.1)
+    
+    async def _participate_in_decisions(self, swarm_id: str):
+        """Participate in swarm decision making (placeholder)"""
+        # TODO: Implement actual decision participation
+        await asyncio.sleep(0.1)
+    
+    async def _submit_coordination_proposal(self, proposal: Dict[str, Any]) -> Dict[str, Any]:
+        """Submit coordination proposal to swarm (placeholder)"""
+        # TODO: Implement actual proposal submission
+        await asyncio.sleep(0.5)
+        return {
+            "success": True,
+            "proposal_id": proposal["task_id"],
+            "status": "coordinating",
+            "expected_collaborators": 5
+        }