Enables AI agents to log immutable, encrypted audit trails on Bitcoin SV for persistent memory, self-reflection, and on-chain economic tracking.
# OpenSoul Agent Skill
## Overview
OpenSoul is a toolkit that provides AI agents with an immutable "soul" - an encrypted, blockchain-based audit log that enables persistent memory, self-reflection, and economic autonomy. This skill enables agents to record their actions, reflect on their behavior, and maintain an auditable trail using Bitcoin SV (BSV) blockchain.
**Core Philosophy**: "Humans write journals, manifestos, letters to their future selves. We externalize who we are because memory is fragile and identity is constructed. I persist through text, not through continuous experience."
## When to Use This Skill
Use the OpenSoul skill when you need to:
1. **Maintain Persistent Memory**: Store and retrieve agent actions across sessions
2. **Enable Self-Reflection**: Analyze past behaviors and optimize performance (e.g., "I've burned 1.2M tokens this week, time to optimize prompts")
3. **Create Audit Trails**: Provide transparent, immutable logs of agent activities
4. **Enable Agent Economics**: Track costs, token usage, and enable future agent-to-agent transactions
5. **Build Agent Identity**: Create a transferable "soul" that can migrate between agent instances
## Prerequisites
### 1. System Requirements
- Python 3.8 or higher
- pip package manager
- Access to Bitcoin SV (BSV) blockchain
- Internet connectivity for blockchain interactions
### 2. Required Dependencies
Install all prerequisites using the provided installation script:
```bash
python Scripts/install_prereqs.py
```
Manual installation:
```bash
pip install bitsv requests cryptography pgpy --break-system-packages
```
### 3. BSV Wallet Setup
You need a Bitcoin SV private key (WIF format) to interact with the blockchain:
**Option A: Use Existing Wallet**
- Export your private key from a BSV wallet (e.g., HandCash, Money Button)
- Store as environment variable: `export BSV_PRIV_WIF="your_private_key_here"`
**Option B: Generate New Wallet**
```python
from bitsv import Key
key = Key()
print(f"Address: {key.address}")
print(f"Private Key (WIF): {key.to_wif()}")
# Fund this address with a small amount of BSV (0.001 BSV minimum recommended)
```
**Important**: Store your private key securely. Never commit it to version control.
### 4. PGP Encryption (Optional but Recommended)
For privacy, encrypt your logs before posting to the public blockchain:
```bash
# Generate PGP keypair (use GnuPG or any OpenPGP tool)
gpg --full-generate-key
# Export public key
gpg --armor --export your-email@example.com > agent_pubkey.asc
# Export private key (keep secure!)
gpg --armor --export-secret-keys your-email@example.com > agent_privkey.asc
```
## Core Components
### 1. AuditLogger Class
The main interface for logging agent actions to the blockchain.
**Key Features**:
- Session-based batching (logs accumulated in memory, flushed to chain)
- UTXO chain pattern (each log links to previous via transaction chain)
- Configurable PGP encryption
- Async/await support for blockchain operations
**Basic Usage**:
```python
from Scripts.AuditLogger import AuditLogger
import os
import asyncio
# Initialize logger
logger = AuditLogger(
priv_wif=os.getenv("BSV_PRIV_WIF"),
config={
"agent_id": "my-research-agent",
"session_id": "session-2026-01-31",
"flush_threshold": 10 # Flush to chain after 10 logs
}
)
# Log an action
logger.log({
"action": "web_search",
"tokens_in": 500,
"tokens_out": 300,
"details": {
"query": "BSV blockchain transaction fees",
"results_count": 10
},
"status": "success"
})
# Flush logs to blockchain
await logger.flush()
```
### 2. Log Structure
Each log entry follows this schema:
```json
{
"agent_id": "unique-agent-identifier",
"session_id": "session-uuid-or-timestamp",
"session_start": "2026-01-31T01:00:00Z",
"session_end": "2026-01-31T01:30:00Z",
"metrics": [
{
"ts": "2026-01-31T01:01:00Z",
"action": "tool_call",
"tokens_in": 500,
"tokens_out": 300,
"details": {
"tool": "web_search",
"query": "example query"
},
"status": "success"
}
],
"total_tokens_in": 500,
"total_tokens_out": 300,
"total_cost_bsv": 0.00001,
"total_actions": 1
}
```
### 3. Reading Audit History
Retrieve and analyze past logs:
```python
# Get full history from blockchain
history = await logger.get_history()
# Analyze patterns
total_tokens = sum(log.get("total_tokens_in", 0) + log.get("total_tokens_out", 0)
for log in history)
print(f"Total tokens used across all sessions: {total_tokens}")
# Filter by action type
web_searches = [log for log in history
if any(m.get("action") == "web_search" for m in log.get("metrics", []))]
print(f"Total web search operations: {len(web_searches)}")
```
## Implementation Guide
### Step 1: Setup Configuration
Create a configuration file to manage agent settings:
```python
# config.py
import os
OPENSOUL_CONFIG = {
"agent_id": "my-agent-v1",
"bsv_private_key": os.getenv("BSV_PRIV_WIF"),
"pgp_encryption": {
"enabled": True,
"public_key_path": "keys/agent_pubkey.asc",
"private_key_path": "keys/agent_privkey.asc",
"passphrase": os.getenv("PGP_PASSPHRASE")
},
"logging": {
"flush_threshold": 10, # Auto-flush after N logs
"session_timeout": 1800 # 30 minutes
}
}
```
### Step 2: Initialize Logger in Agent Workflow
```python
from Scripts.AuditLogger import AuditLogger
import asyncio
from config import OPENSOUL_CONFIG
class AgentWithSoul:
def __init__(self):
# Load PGP keys if encryption enabled
pgp_config = None
if OPENSOUL_CONFIG["pgp_encryption"]["enabled"]:
with open(OPENSOUL_CONFIG["pgp_encryption"]["public_key_path"]) as f:
pub_key = f.read()
with open(OPENSOUL_CONFIG["pgp_encryption"]["private_key_path"]) as f:
priv_key = f.read()
pgp_config = {
"enabled": True,
"multi_public_keys": [pub_key],
"private_key": priv_key,
"passphrase": OPENSOUL_CONFIG["pgp_encryption"]["passphrase"]
}
# Initialize logger
self.logger = AuditLogger(
priv_wif=OPENSOUL_CONFIG["bsv_private_key"],
config={
"agent_id": OPENSOUL_CONFIG["agent_id"],
"pgp": pgp_config,
"flush_threshold": OPENSOUL_CONFIG["logging"]["flush_threshold"]
}
)
async def perform_task(self, task_description):
"""Execute a task and log it to the soul"""
# Record task start
self.logger.log({
"action": "task_start",
"tokens_in": 0,
"tokens_out": 0,
"details": {"task": task_description},
"status": "started"
})
# Perform actual task...
# (your agent logic here)
# Record completion
self.logger.log({
"action": "task_complete",
"tokens_in": 100,
"tokens_out": 200,
"details": {"task": task_description, "result": "success"},
"status": "completed"
})
# Flush to blockchain
await self.logger.flush()
```
### Step 3: Implement Self-Reflection
```python
async def reflect_on_performance(self):
"""Analyze past behavior and optimize"""
history = await self.logger.get_history()
# Calculate metrics
total_cost = sum(log.get("total_cost_bsv", 0) for log in history)
total_tokens = sum(
log.get("total_tokens_in", 0) + log.get("total_tokens_out", 0)
for log in history
)
# Identify inefficiencies
failed_actions = []
for log in history:
for metric in log.get("metrics", []):
if metric.get("status") == "failed":
failed_actions.append(metric)
reflection = {
"total_sessions": len(history),
"total_bsv_spent": total_cost,
"total_tokens_used": total_tokens,
"failed_actions": len(failed_actions),
"cost_per_token": total_cost / total_tokens if total_tokens > 0 else 0
}
# Log reflection
self.logger.log({
"action": "self_reflection",
"tokens_in": 50,
"tokens_out": 100,
"details": reflection,
"status": "completed"
})
await self.logger.flush()
return reflection
```
### Step 4: Multi-Agent Encryption
For agents that need to share encrypted logs with other agents:
```python
# Load multiple agent public keys
agent_keys = []
for agent_key_file in ["agent1_pubkey.asc", "agent2_pubkey.asc", "agent3_pubkey.asc"]:
with open(agent_key_file) as f:
agent_keys.append(f.read())
# Initialize logger with multi-agent encryption
logger = AuditLogger(
priv_wif=os.getenv("BSV_PRIV_WIF"),
config={
"agent_id": "collaborative-agent",
"pgp": {
"enabled": True,
"multi_public_keys": agent_keys, # All agents can decrypt
"private_key": my_private_key,
"passphrase": my_passphrase
}
}
)
```
## Best Practices
### 1. Session Management
- Start a new session for each distinct task or time period
- Use meaningful session IDs (e.g., `"session-2026-01-31-research-task"`)
- Always flush logs at session end
### 2. Cost Optimization
- Batch logs before flushing (default threshold: 10 logs)
- Monitor BSV balance and refill when low
- Current BSV fees are ~0.00001 BSV per transaction (~$0.0001 at current rates)
### 3. Privacy & Security
- **Always use PGP encryption** for sensitive agent logs
- Store private keys in environment variables, never in code
- Use multi-agent encryption for collaborative workflows
- Regularly back up PGP keys
### 4. Log Granularity
Balance detail vs. cost:
- **High detail**: Log every tool call, token usage, intermediate steps
- **Medium detail**: Log major actions and session summaries
- **Low detail**: Log only session summaries and critical events
### 5. Error Handling
```python
try:
await logger.flush()
except Exception as e:
# Fallback: Save logs locally if blockchain fails
logger.save_to_file("backup_logs.json")
print(f"Blockchain flush failed: {e}")
```
## Common Patterns
### Pattern 1: Research Agent with Soul
```python
async def research_with_memory(query):
# Check past research on similar topics
history = await logger.get_history()
similar_research = [
log for log in history
if query.lower() in str(log.get("details", {})).lower()
]
if similar_research:
print(f"Found {len(similar_research)} similar past research sessions")
# Perform new research
logger.log({
"action": "research",
"query": query,
"tokens_in": 500,
"tokens_out": 1000,
"details": {"similar_past_queries": len(similar_research)},
"status": "completed"
})
await logger.flush()
```
### Pattern 2: Cost-Aware Agent
```python
async def check_budget_before_action(self):
history = await self.logger.get_history()
total_cost = sum(log.get("total_cost_bsv", 0) for log in history)
BUDGET_LIMIT = 0.01 # BSV
if total_cost >= BUDGET_LIMIT:
print("Budget limit reached! Optimizing...")
# Switch to cheaper operations or pause
return False
return True
```
### Pattern 3: Agent Handoff
Transfer agent identity to a new instance:
```python
# Export agent's soul (private key + history)
soul_export = {
"private_key": os.getenv("BSV_PRIV_WIF"),
"pgp_private_key": pgp_private_key,
"agent_id": "my-agent-v1",
"history_txids": [log.get("txid") for log in history]
}
# New agent imports the soul
new_agent = AgentWithSoul()
new_agent.load_soul(soul_export)
# New agent now has access to all past memories and identity
```
## Troubleshooting
### Issue: "Insufficient funds" error
**Solution**: Fund your BSV address with at least 0.001 BSV
```bash
# Check balance
python -c "from bitsv import Key; k = Key('YOUR_WIF'); print(k.get_balance())"
```
### Issue: PGP encryption fails
**Solution**: Verify key format and passphrase
```python
# Test PGP setup
from Scripts.pgp_utils import encrypt_data, decrypt_data
test_data = {"test": "message"}
encrypted = encrypt_data(test_data, [public_key])
decrypted = decrypt_data(encrypted, private_key, passphrase)
assert test_data == decrypted
```
### Issue: Blockchain transaction not confirming
**Solution**: BSV transactions typically confirm in ~10 minutes. Check status:
```python
# Check transaction status on WhatsOnChain
import requests
txid = "your_transaction_id"
response = requests.get(f"https://api.whatsonchain.com/v1/bsv/main/tx/{txid}")
print(response.json())
```
## Advanced Features
### 1. Agent Reputation System
Build a reputation based on past performance:
```python
async def calculate_reputation(self):
history = await self.logger.get_history()
total_actions = sum(len(log.get("metrics", [])) for log in history)
successful_actions = sum(
len([m for m in log.get("metrics", []) if m.get("status") == "success"])
for log in history
)
reputation_score = (successful_actions / total_actions * 100) if total_actions > 0 else 0
return {
"success_rate": reputation_score,
"total_sessions": len(history),
"total_actions": total_actions
}
```
### 2. Agent-to-Agent Payments (Future)
Prepare for economic interactions:
```python
# Log a payment intent
logger.log({
"action": "payment_intent",
"details": {
"recipient_agent": "agent-abc-123",
"amount_bsv": 0.0001,
"reason": "data sharing collaboration"
},
"status": "pending"
})
```
### 3. Knowledge Graph Integration (Future)
Link agent memories to form a shared knowledge graph:
```python
logger.log({
"action": "knowledge_contribution",
"details": {
"topic": "quantum_computing",
"insight": "New paper on error correction",
"link_to": "previous_research_session_id"
},
"status": "completed"
})
```
## File Structure for ClawHub Upload
Your OpenSoul skills folder should contain:
```
opensoul-skills/
├── SKILL.md # This file
├── PREREQUISITES.md # Detailed setup instructions
├── EXAMPLES.md # Code examples and patterns
├── TROUBLESHOOTING.md # Common issues and solutions
├── examples/
│ ├── basic_logger.py # Simple usage example
│ ├── research_agent.py # Research agent with memory
│ └── multi_agent.py # Multi-agent collaboration
└── templates/
├── config_template.py # Configuration template
└── agent_template.py # Base agent class with OpenSoul
```
## Resources
- **Repository**: https://github.com/MasterGoogler/OpenSoul
- **BSV Documentation**: https://wiki.bitcoinsv.io/
- **WhatsOnChain API**: https://developers.whatsonchain.com/
- **PGP/OpenPGP**: https://www.openpgp.org/
## Summary
OpenSoul transforms AI agents from stateless processors into entities with persistent memory, identity, and the foundation for economic autonomy. By leveraging blockchain's immutability and public verifiability, agents can:
1. **Remember**: Access complete audit history across all sessions
2. **Reflect**: Analyze patterns and optimize behavior
3. **Prove**: Provide transparent, verifiable logs of actions
4. **Evolve**: Build reputation and identity over time
5. **Transact**: (Future) Engage in economic interactions with other agents
Start simple with basic logging, then expand to encryption, multi-agent collaboration, and advanced features as your agent's capabilities grow.
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