自主工作系统

cd /Users/evanpaliotta/199os-autonomous-worker
pip install -r requirements.txt

cp .env.example .env
# Edit .env and add:
# - ANTHROPIC_API_KEY
# - DATABASE_URL (PostgreSQL)
# - SLACK_BOT_TOKEN or SLACK_WEBHOOK_URL
# - SMTP credentials (for email alerts)

python -c "from src.state.database import DatabaseManager; DatabaseManager().init_db()"

python run_worker.py run customer_health_monitor

python run_worker.py start

┌─────────────────────────────────────────────┐
│         Scheduler (APScheduler)             │
│     Triggers workers on cron schedules      │
└─────────────────────────────────────────────┘
                    │
                    ▼
┌─────────────────────────────────────────────┐
│      Worker Orchestrator                    │
│  • Loads MCP servers dynamically            │
│  • Calls Anthropic API (user's model)       │
│  • Parses responses, triggers actions       │
│  • Tracks costs, deduplicates alerts        │
└─────────────────────────────────────────────┘
                    │
        ┌───────────┼───────────┐
        ▼           ▼           ▼
    ┌─────┐    ┌─────┐    ┌─────┐
    │Sales│    │Mktg │    │ CS  │ (MCP Servers)
    │ MCP │    │ MCP │    │ MCP │
    └─────┘    └─────┘    └─────┘
                    │
        ┌───────────┼───────────────┐
        ▼           ▼               ▼
   [PostgreSQL] [Slack API]  [Email SMTP]
   (State)      (Alerts)     (Reports)

workers:
  - name: my_custom_worker
    description: Monitor X and alert on Y
    server: sales  # or marketing, customer_success
    model: claude-3-5-sonnet-20241022  # YOU choose the model
    schedule: "0 */4 * * *"  # Cron expression
    enabled: true
    max_tokens: 50000
    temperature: 1.0

    prompt: |
      Your detailed task instructions here.
      The worker will use the specified MCP server tools.

    actions:
      - type: slack
        config:
          channel: "#alerts"
        threshold: high_priority  # or any_alerts, any_findings

      - type: email
        config:
          to:
            - team@company.com
          subject: "Alert: {worker_name}"
        threshold: high_priority

    metadata:
      category: sales
      priority: high

max_monthly_cost_usd: 5000.0  # Hard limit
max_concurrent_workers: 5
retry_attempts: 3
alert_deduplication_hours: 24  # Don't spam same alert

# Set monthly budget (system stops when exceeded)
max_monthly_cost_usd: 5000.0

# Per-worker token limits
max_tokens: 50000  # Prevents runaway costs

# Model selection affects cost
model: claude-3-5-sonnet-20241022  # $3/$15 per 1M tokens
model: claude-3-5-haiku-20241022   # $0.8/$4 per 1M tokens (80% cheaper!)

# View current spend
python run_worker.py status

# Output:
# 💰 Budget:
#   Monthly Cost: $1,234.56
#   Remaining: $3,765.44
#   Utilization: 24.7%

python run_worker.py run customer_health_monitor

python run_worker.py start

python run_worker.py status

python run_worker.py list

from src.state.database import DatabaseManager

db = DatabaseManager()
runs = db.get_recent_runs(limit=10)
for run in runs:
    print(f"{run['worker_name']}: {run['status']} - ${run['cost_usd']}")

actions:
  - type: slack
    config:
      channel: "#customer-alerts"
      # Uses SLACK_BOT_TOKEN or SLACK_WEBHOOK_URL from .env
    threshold: high_priority

actions:
  - type: email
    config:
      to:
        - team@company.com
        - manager@company.com
      subject: "[URGENT] {worker_name} Alert"
    threshold: any_alerts

actions:
  - type: webhook
    config:
      url: "https://your-api.com/alerts"
      method: POST
      headers:
        Authorization: "Bearer YOUR_TOKEN"

# Get worker stats
db.get_worker_stats("customer_health_monitor", days=30)

# Check monthly cost
monthly_cost = db.get_monthly_cost()

# Should we send this alert? (deduplication)
should_send = db.should_send_alert(
    worker_name="deal_risk_analyzer",
    alert_key="deal:12345:high_risk",
    deduplication_hours=24
)

name: competitor_price_monitor
description: Track competitor pricing changes
server: marketing
model: claude-3-5-haiku-20241022  # Cheap for frequent checks
schedule: "0 */2 * * *"  # Every 2 hours
enabled: true

prompt: |
  Use the Marketing MCP tools to:
  1. Fetch competitor pricing pages
  2. Compare to our pricing
  3. Identify any changes in last 24h
  4. Calculate price gap percentage

  Alert if competitor drops prices >10%.

actions:
  - type: slack
    config:
      channel: "#competitive-intel"
    threshold: any_alerts

python run_worker.py run competitor_price_monitor

python run_worker.py start

python run_worker.py start

sudo cp infrastructure/systemd/autonomous-worker.service /etc/systemd/system/
sudo systemctl enable autonomous-worker
sudo systemctl start autonomous-worker
sudo systemctl status autonomous-worker

docker-compose up -d
docker-compose logs -f

# SSH into instance
git clone <your-repo>
cd 199os-autonomous-worker
pip install -r requirements.txt
cp .env.example .env
# Edit .env
python run_worker.py start

# Use tmux/screen to keep running
tmux new -s workers
python run_worker.py start
# Ctrl+B, D to detach

{
  "timestamp": "2025-10-14T12:00:00Z",
  "level": "info",
  "event": "worker_completed",
  "worker": "customer_health_monitor",
  "status": "success",
  "cost_usd": 0.1234,
  "actions": 2
}