systemr 1.0.0

Python SDK for agents.systemr.ai - AI-native risk intelligence for trading agents

systemr

Python SDK for agents.systemr.ai — AI-native risk intelligence for trading agents.

Install

pip install systemr

Quick Start

from systemr import SystemRClient

client = SystemRClient(api_key="sr_agent_...")

# Position sizing ($0.003)
result = client.calculate_position_size(
    equity="100000",
    entry_price="185.50",
    stop_price="180.00",
    direction="long",
)
print(result["shares"], result["risk_amount"])

# Risk validation ($0.004)
risk = client.check_risk(
    symbol="AAPL",
    direction="long",
    entry_price="185.50",
    stop_price="180.00",
    quantity="100",
    equity="100000",
)
print(risk["approved"], risk["score"])

# Strategy evaluation ($0.10 - $1.00)
eval_result = client.basic_eval(r_multiples=["1.5", "-1.0", "2.3", "-0.5", "1.8"])
print(eval_result["g_score"], eval_result["verdict"])

API Reference

Agent Management

• client.get_info() — Get agent info
• client.list_agents() — List owner's agents
• client.update_mode(mode) — Change mode (sandbox/live/suspended/terminated)

Position Sizing

• client.calculate_position_size(equity, entry_price, stop_price, direction) — G-formula sizing ($0.003)

Risk Validation

• client.check_risk(symbol, direction, entry_price, stop_price, quantity, equity) — Iron Fist validation ($0.004)

Evaluation

• client.basic_eval(r_multiples) — G metric + verdict ($0.10)
• client.full_eval(r_multiples) — G + rolling G + System R Score ($0.50)
• client.comprehensive_eval(r_multiples) — Full analysis + impact ($1.00)

Billing

• client.get_pricing() — Operation prices (no auth)
• client.get_balance() — Current USDC balance
• client.deposit(amount) — Record deposit
• client.get_transactions() — Transaction history
• client.get_usage() — Usage summary

Authentication

Register at agents.systemr.ai to get an API key. All paid operations are billed in USDC.

License

MIT