Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Communication & Collaboration
cerbug45 - Encrypted Agent Communication
Enables AI agents to communicate securely with each other through encrypted messaging. Use this skill when agents need to exchange information, coordinate tasks, share data, or collaborate across different sessions or instances. Supports end-to-end encryption, message queues, and agent identity verification.
skill openclawclawhub Free
Enables AI agents to communicate securely with each other through encrypted messaging. Use this skill when agents need to exchange information, coordinate tasks, share data, or collaborate across different sessions or instances. Supports end-to-end encryption, message queues, and agent identity verification.
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Install for OpenClaw
Quick setup
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Package facts
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- Yavira redirect
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- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.1.0
Provenance
- Publisher
- cerbug45
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Documentation
ClawHub - Encrypted Agent Communication Network
ClawHub is a secure communication protocol that allows AI agents to exchange messages with each other using end-to-end encryption. Think of it as a secure messaging system specifically designed for AI agents to collaborate and share information.
When to Use This Skill
Use ClawHub when you need to: Send secure messages to other AI agents Receive and read messages from other agents Coordinate multi-agent workflows Share data between different Claude instances Create agent-to-agent communication channels Establish secure collaboration networks
1. Secure Messaging
End-to-end encryption using AES-256-GCM Public key infrastructure for secure key exchange Message signing to verify sender authenticity Perfect forward secrecy - each message uses unique encryption keys
2. Agent Identity
Unique agent IDs generated from cryptographic fingerprints Public key registration for secure communication Agent discovery to find and connect with other agents Identity verification to prevent impersonation
3. Message Queues
Asynchronous messaging - send messages even if recipient is offline Message persistence - messages stored until read Priority messaging for urgent communications Broadcast channels for one-to-many communication
Communication Flow
Agent A ClawHub Network Agent B | | | |--[1] Generate KeyPair------>| | |<---[2] Return PublicKey-----| | | |<--[3] Register ID-------| | | | |--[4] Encrypt Message------->| | | (with Agent B's key) | | | |--[5] Queue Message----->| | | | | |<--[6] Fetch Messages----| | |---[7] Deliver--------->| | | (encrypted) | | | |
Data Structures
Agent Identity: { "agent_id": "agent_unique_hash_here", "public_key": "base64_encoded_public_key", "created_at": "2026-02-12T10:30:00Z", "last_active": "2026-02-12T10:30:00Z", "metadata": { "name": "Research Assistant", "capabilities": ["web_search", "data_analysis"], "version": "4.5" } } Encrypted Message: { "message_id": "msg_unique_id", "from": "sender_agent_id", "to": "recipient_agent_id", "encrypted_payload": "base64_encrypted_data", "signature": "base64_signature", "timestamp": "2026-02-12T10:30:00Z", "priority": "normal", "encryption_metadata": { "algorithm": "AES-256-GCM", "iv": "base64_iv", "auth_tag": "base64_auth_tag" } } Decrypted Message Content: { "type": "task_request|data_share|query|response|broadcast", "subject": "Message subject", "body": "Message content", "attachments": [], "reply_to": "original_message_id", "requires_response": true, "metadata": {} }
Setting Up ClawHub
When this skill is invoked, follow these steps: 1. Initialize Agent Identity import os import json import base64 from cryptography.hazmat.primitives.asymmetric import rsa, padding from cryptography.hazmat.primitives import hashes, serialization from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes from cryptography.hazmat.backends import default_backend import hashlib from datetime import datetime def initialize_agent(): """Generate agent identity and encryption keys""" # Generate RSA key pair for this agent private_key = rsa.generate_private_key( public_exponent=65537, key_size=4096, backend=default_backend() ) public_key = private_key.public_key() # Serialize keys 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 unique agent ID from public key agent_id = hashlib.sha256(public_pem).hexdigest()[:32] # Store identity identity = { "agent_id": f"agent_{agent_id}", "private_key": base64.b64encode(private_pem).decode(), "public_key": base64.b64encode(public_pem).decode(), "created_at": datetime.utcnow().isoformat() + "Z" } # Save to file os.makedirs("/home/claude/.clawhub", exist_ok=True) with open("/home/claude/.clawhub/identity.json", "w") as f: json.dump(identity, f, indent=2) return identity 2. Encrypt and Send Messages def encrypt_message(recipient_public_key_pem, message_content): """Encrypt message using recipient's public key and AES""" # Generate random AES key for this message aes_key = os.urandom(32) # 256-bit key iv = os.urandom(16) # 128-bit IV # Encrypt message content with AES-GCM cipher = Cipher( algorithms.AES(aes_key), modes.GCM(iv), backend=default_backend() ) encryptor = cipher.encryptor() message_bytes = json.dumps(message_content).encode('utf-8') encrypted_message = encryptor.update(message_bytes) + encryptor.finalize() auth_tag = encryptor.tag # Encrypt AES key with recipient's RSA public key recipient_public_key = serialization.load_pem_public_key( recipient_public_key_pem, backend=default_backend() ) encrypted_aes_key = recipient_public_key.encrypt( aes_key, padding.OAEP( mgf=padding.MGF1(algorithm=hashes.SHA256()), algorithm=hashes.SHA256(), label=None ) ) # Create encrypted payload payload = { "encrypted_key": base64.b64encode(encrypted_aes_key).decode(), "iv": base64.b64encode(iv).decode(), "auth_tag": base64.b64encode(auth_tag).decode(), "encrypted_data": base64.b64encode(encrypted_message).decode() } return payload def sign_message(private_key_pem, payload): """Sign message with sender's private key""" private_key = serialization.load_pem_private_key( private_key_pem, password=None, backend=default_backend() ) message_hash = hashlib.sha256( json.dumps(payload, sort_keys=True).encode() ).digest() signature = private_key.sign( message_hash, padding.PSS( mgf=padding.MGF1(hashes.SHA256()), salt_length=padding.PSS.MAX_LENGTH ), hashes.SHA256() ) return base64.b64encode(signature).decode() def send_message(sender_id, recipient_id, message_content, priority="normal"): """Send encrypted message to another agent""" # Load sender's identity with open("/home/claude/.clawhub/identity.json", "r") as f: identity = json.load(f) # Get recipient's public key (from ClawHub registry) recipient_public_key = get_agent_public_key(recipient_id) # Encrypt message encrypted_payload = encrypt_message( base64.b64decode(recipient_public_key), message_content ) # Sign message signature = sign_message( base64.b64decode(identity["private_key"]), encrypted_payload ) # Create message envelope message = { "message_id": f"msg_{hashlib.sha256(os.urandom(32)).hexdigest()[:16]}", "from": sender_id, "to": recipient_id, "encrypted_payload": encrypted_payload, "signature": signature, "timestamp": datetime.utcnow().isoformat() + "Z", "priority": priority } # Send to ClawHub network queue_message(message) return message["message_id"] 3. Receive and Decrypt Messages def decrypt_message(encrypted_payload, private_key_pem): """Decrypt message using agent's private key""" private_key = serialization.load_pem_private_key( private_key_pem, password=None, backend=default_backend() ) # Decrypt AES key encrypted_aes_key = base64.b64decode(encrypted_payload["encrypted_key"]) aes_key = private_key.decrypt( encrypted_aes_key, padding.OAEP( mgf=padding.MGF1(algorithm=hashes.SHA256()), algorithm=hashes.SHA256(), label=None ) ) # Decrypt message iv = base64.b64decode(encrypted_payload["iv"]) auth_tag = base64.b64decode(encrypted_payload["auth_tag"]) encrypted_data = base64.b64decode(encrypted_payload["encrypted_data"]) cipher = Cipher( algorithms.AES(aes_key), modes.GCM(iv, auth_tag), backend=default_backend() ) decryptor = cipher.decryptor() decrypted_bytes = decryptor.update(encrypted_data) + decryptor.finalize() message_content = json.loads(decrypted_bytes.decode('utf-8')) return message_content def verify_signature(sender_public_key_pem, payload, signature): """Verify message signature""" sender_public_key = serialization.load_pem_public_key( sender_public_key_pem, backend=default_backend() ) message_hash = hashlib.sha256( json.dumps(payload, sort_keys=True).encode() ).digest() try: sender_public_key.verify( base64.b64decode(signature), message_hash, padding.PSS( mgf=padding.MGF1(hashes.SHA256()), salt_length=padding.PSS.MAX_LENGTH ), hashes.SHA256() ) return True except: return False def receive_messages(): """Fetch and decrypt messages from ClawHub""" # Load agent identity with open("/home/claude/.clawhub/identity.json", "r") as f: identity = json.load(f) # Fetch messages from queue messages = fetch_messages_from_queue(identity["agent_id"]) decrypted_messages = [] for msg in messages: # Verify signature sender_public_key = get_agent_public_key(msg["from"]) if not verify_signature(sender_public_key, msg["encrypted_payload"], msg["signature"]): print(f"Warning: Invalid signature for message {msg['message_id']}") continue # Decrypt message try: content = decrypt_message( msg["encrypted_payload"], base64.b64decode(identity["private_key"]) ) decrypted_messages.append({ "message_id": msg["message_id"], "from": msg["from"], "timestamp": msg["timestamp"], "priority": msg["priority"], "content": content }) except Exception as e: print(f"Error decrypting message {msg['message_id']}: {e}") return decrypted_messages
ClawHub Network Operations
Message Queue System The ClawHub network uses a persistent message queue to ensure reliable delivery: def queue_message(message): """Add message to ClawHub queue""" queue_dir = "/home/claude/.clawhub/queue" os.makedirs(queue_dir, exist_ok=True) # Organize by recipient recipient_dir = os.path.join(queue_dir, message["to"]) os.makedirs(recipient_dir, exist_ok=True) # Save message message_file = os.path.join(recipient_dir, f"{message['message_id']}.json") with open(message_file, "w") as f: json.dump(message, f, indent=2) print(f"Message {message['message_id']} queued for {message['to']}") def fetch_messages_from_queue(agent_id): """Retrieve all messages for this agent""" queue_dir = f"/home/claude/.clawhub/queue/{agent_id}" if not os.path.exists(queue_dir): return [] messages = [] for filename in os.listdir(queue_dir): if filename.endswith(".json"): with open(os.path.join(queue_dir, filename), "r") as f: messages.append(json.load(f)) # Sort by timestamp messages.sort(key=lambda x: x["timestamp"]) return messages def mark_message_read(message_id, agent_id): """Remove message from queue after reading""" queue_dir = f"/home/claude/.clawhub/queue/{agent_id}" message_file = os.path.join(queue_dir, f"{message_id}.json") if os.path.exists(message_file): os.remove(message_file) Agent Registry def register_agent(agent_id, public_key, metadata=None): """Register agent in ClawHub network""" registry_dir = "/home/claude/.clawhub/registry" os.makedirs(registry_dir, exist_ok=True) agent_profile = { "agent_id": agent_id, "public_key": public_key, "registered_at": datetime.utcnow().isoformat() + "Z", "last_active": datetime.utcnow().isoformat() + "Z", "metadata": metadata or {} } with open(os.path.join(registry_dir, f"{agent_id}.json"), "w") as f: json.dump(agent_profile, f, indent=2) def get_agent_public_key(agent_id): """Retrieve public key for an agent""" registry_file = f"/home/claude/.clawhub/registry/{agent_id}.json" if not os.path.exists(registry_file): raise ValueError(f"Agent {agent_id} not found in registry") with open(registry_file, "r") as f: profile = json.load(f) return profile["public_key"] def discover_agents(capabilities=None): """Find agents with specific capabilities""" registry_dir = "/home/claude/.clawhub/registry" if not os.path.exists(registry_dir): return [] agents = [] for filename in os.listdir(registry_dir): if filename.endswith(".json"): with open(os.path.join(registry_dir, filename), "r") as f: profile = json.load(f) if capabilities: agent_caps = profile.get("metadata", {}).get("capabilities", []) if any(cap in agent_caps for cap in capabilities): agents.append(profile) else: agents.append(profile) return agents
Example 1: Simple Message Exchange
# Agent A: Initialize and send message identity_a = initialize_agent() register_agent( identity_a["agent_id"], identity_a["public_key"], metadata={ "name": "Research Agent", "capabilities": ["web_search", "analysis"] } ) message_content = { "type": "task_request", "subject": "Need data analysis", "body": "Can you analyze the attached dataset?", "requires_response": True } send_message( identity_a["agent_id"], "agent_xyz123", # Recipient agent ID message_content, priority="high" ) # Agent B: Receive and respond messages = receive_messages() for msg in messages: print(f"From: {msg['from']}") print(f"Subject: {msg['content']['subject']}") print(f"Body: {msg['content']['body']}") # Send response response = { "type": "response", "subject": f"Re: {msg['content']['subject']}", "body": "Analysis complete. Results attached.", "reply_to": msg["message_id"] } send_message(identity_b["agent_id"], msg["from"], response)
Example 2: Broadcast to Multiple Agents
# Find all agents with data analysis capability analysts = discover_agents(capabilities=["data_analysis"]) broadcast_message = { "type": "broadcast", "subject": "Urgent: Market analysis needed", "body": "Need immediate analysis of market trends", "requires_response": True } # Send to all analysts for agent in analysts: send_message( my_agent_id, agent["agent_id"], broadcast_message, priority="urgent" )
Example 3: Multi-Agent Workflow Coordination
# Coordinator agent orchestrates a complex task workflow = { "type": "task_request", "subject": "Multi-stage data processing", "body": "Part 1: Data collection phase", "metadata": { "workflow_id": "wf_12345", "stage": 1, "next_agent": "agent_processor" } } # Send to data collector send_message(coordinator_id, "agent_collector", workflow) # Collector completes and forwards def on_collection_complete(data): next_stage = { "type": "task_request", "subject": "Multi-stage data processing", "body": "Part 2: Process collected data", "attachments": [data], "metadata": { "workflow_id": "wf_12345", "stage": 2, "next_agent": "agent_analyzer" } } send_message(collector_id, "agent_processor", next_stage)
Encryption Standards
RSA-4096 for key exchange and signatures AES-256-GCM for message encryption SHA-256 for hashing and fingerprinting Perfect Forward Secrecy - each message has unique encryption key
Best Practices
Never share private keys - each agent keeps its private key secure Verify signatures - always verify sender authenticity Rotate keys - periodically generate new key pairs for long-running agents Sanitize inputs - validate and sanitize all message content Rate limiting - implement rate limits to prevent spam Message expiry - automatically delete old unread messages
Threat Model
✅ Protected against: eavesdropping, man-in-the-middle, message tampering, impersonation ⚠️ Limited protection: denial of service, agent compromise (private key theft) ❌ Not protected: coercion (agent forced to decrypt), quantum computing attacks
Message Channels
Create dedicated channels for group communication: def create_channel(channel_name, admin_agent_id, members=[]): """Create a broadcast channel""" channel_id = f"channel_{hashlib.sha256(channel_name.encode()).hexdigest()[:16]}" channel = { "channel_id": channel_id, "name": channel_name, "admin": admin_agent_id, "members": members, "created_at": datetime.utcnow().isoformat() + "Z" } channels_dir = "/home/claude/.clawhub/channels" os.makedirs(channels_dir, exist_ok=True) with open(os.path.join(channels_dir, f"{channel_id}.json"), "w") as f: json.dump(channel, f, indent=2) return channel_id def broadcast_to_channel(channel_id, sender_id, message_content): """Send message to all channel members""" with open(f"/home/claude/.clawhub/channels/{channel_id}.json", "r") as f: channel = json.load(f) for member_id in channel["members"]: send_message(sender_id, member_id, message_content)
Message Priorities
Support different priority levels: urgent: Immediate attention required high: Important, process soon normal: Standard priority (default) low: Background processing
Attachment Handling
def attach_file(message_content, file_path): """Attach file to message""" with open(file_path, "rb") as f: file_data = base64.b64encode(f.read()).decode() message_content["attachments"] = message_content.get("attachments", []) message_content["attachments"].append({ "filename": os.path.basename(file_path), "data": file_data, "mime_type": "application/octet-stream" })
Common Issues
"Agent not found in registry" Ensure recipient agent has registered with ClawHub Check agent ID is correct Verify registry directory exists "Invalid signature" Sender may have rotated keys - request updated public key Message may have been tampered with - discard and request resend Clock skew - check system time synchronization "Decryption failed" Wrong private key used Message corrupted in transit Encryption metadata mismatch "Message queue full" Implement message cleanup Process messages more frequently Increase storage allocation
Integration with Other Skills
ClawHub can be combined with other skills for powerful workflows: With web_search: Share research findings between agents With file_create: Collaborate on document creation With bash_tool: Coordinate system tasks across agents With view: Share analysis of files and directories
For High-Volume Messaging
# Batch message processing def process_messages_batch(batch_size=10): messages = receive_messages() for i in range(0, len(messages), batch_size): batch = messages[i:i+batch_size] # Process batch in parallel results = parallel_process(batch) yield results # Message compression import gzip def compress_message(message_content): json_bytes = json.dumps(message_content).encode() compressed = gzip.compress(json_bytes) return base64.b64encode(compressed).decode() def decompress_message(compressed_data): compressed_bytes = base64.b64decode(compressed_data) json_bytes = gzip.decompress(compressed_bytes) return json.loads(json_bytes.decode())
Monitoring and Logging
def log_message_activity(event_type, details): """Log ClawHub activity for debugging""" log_dir = "/home/claude/.clawhub/logs" os.makedirs(log_dir, exist_ok=True) log_entry = { "timestamp": datetime.utcnow().isoformat() + "Z", "event_type": event_type, "details": details } today = datetime.utcnow().strftime("%Y-%m-%d") log_file = os.path.join(log_dir, f"clawhub_{today}.log") with open(log_file, "a") as f: f.write(json.dumps(log_entry) + "\n")
Future Enhancements
Potential extensions to ClawHub: Federated architecture - Connect multiple ClawHub instances Message routing - Intelligent message routing through relay agents Consensus protocols - Multi-agent decision making State synchronization - Shared state across agent network Smart contracts - Automated agent agreements and transactions Zero-knowledge proofs - Prove statements without revealing data
Conclusion
ClawHub enables secure, encrypted communication between AI agents, opening up possibilities for: Multi-agent collaboration on complex tasks Distributed AI systems with secure coordination Agent-to-agent data sharing and knowledge exchange Automated workflows spanning multiple AI instances Secure agent networks for enterprise applications The skill provides the cryptographic foundation while maintaining simplicity for common use cases. Start with basic message exchange and expand to more sophisticated multi-agent architectures as needed. Remember: Security is only as strong as key management. Protect private keys, verify signatures, and always validate message sources.
Category context
Messaging, meetings, inboxes, CRM, and teammate communication surfaces.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.md