How to set guardrails for a trading agent

A trading agent connected to a single API can place orders across stocks, crypto, perpetual futures, options, and prediction markets using real money from your own wallet. Without guardrails, an agent can lose capital rapidly by misinterpreting signals, repeating mistakes, or trading outside your intended strategy. Effective guardrails restrict which markets the agent can access, how much it can spend, and how you can stop it before any order reaches a market. They are the difference between a controlled experiment and an uncontrolled liability.

What does a trading agent control through one API?

The Felix API normalizes access across five distinct market types. Instead of building separate integrations for a stock broker, a crypto exchange, a perps venue, an options venue, and a prediction market, you connect once and trade everywhere. The agent sees a unified interface where orders are sized in plain US dollars, removing the need for venue-specific contract math or notional calculations. This convenience is powerful, but it also means a single key can move value into many instruments across different asset classes. That breadth makes guardrails essential, because a mistake in one market can ripple through your overall balance before you have time to react.

Funds remain non-custodial by construction. The agent trades from a wallet you control, and withdrawal addresses are owner-approved only. The agent cannot send funds to itself, cannot add new withdrawal destinations, and cannot steal capital. It can only trade within the boundaries you set, and it can only spend what you authorize. This model means the API acts as a control layer rather than a custodian, but the control is only as strong as the limits you configure. If you grant too much scope, the agent has too much room to err.

Why do beginners underestimate the speed of agent errors?

Beginners often assume an agent will behave like a cautious human who pauses to reconsider a losing trade. Agents do not pause. They execute logic as fast as the API allows, and they do not feel uncertainty. Suppose an agent receives a stale price feed and decides to increase a losing position instead of closing it. Without a position limit or a budget cap, that loop can continue until the allocated capital is exhausted. Trading can lose money, including everything, and an unchecked agent can do so in minutes, not days.

Another common gap is confusing paper trading results with live behavior. In paper mode, slippage and partial fills are simulated using reasonable assumptions that do not always match reality. In live trading, liquidity gaps, sudden volatility, and venue-specific idiosyncrasies can produce sharply different outcomes than what you observed in testing. The transition from paper to live is where many beginners discover that their agent's logic is too aggressive or that its signal is noisier than expected. This is why guardrails must be tested thoroughly in paper mode and then enforced strictly when the key is authorized for live trading. You should never increase a live budget until the agent has demonstrated predictable behavior under real conditions over multiple sessions.

How do scoped keys and budget caps work?

Scoped keys restrict which actions an agent can perform through the API. You might create a key that can trade crypto and perps but cannot access options or prediction markets. You might further restrict it to long-only positions, or to a specific maximum position size per trade. Budget caps are hard dollar limits on total exposure or daily spend. Once the cap is reached, the API rejects further orders automatically and logs the attempt. These limits are not suggestions or warnings; they are enforced at the API level before the order ever reaches a market.

Position limits complement budget caps by capping the size of any single trade or open position. This prevents an agent from concentrating too much capital in one instrument after a misread. Withdrawal controls add another layer: even if the agent is compromised, it cannot move funds out of your wallet because the destination addresses are fixed and owner-approved. You can learn more about the mechanics in How to build scoped API keys for a trading agent step by step. These layers work together so that no single failure mode can drain your account.

• ·Which market types the agent can access, such as stocks or perpetual futures.
• ·Whether the agent can open long positions, short positions, or both.
• ·The maximum dollar value of any single order or open position.
• ·The total daily or weekly budget the agent can deploy across all markets.
• ·The specific wallet or sub-account the agent is allowed to trade from.

What is a kill switch and when do you use it?

A kill switch is a panic control that flattens open positions and revokes the agent's API key in a single action. It is designed to stop trading immediately when behavior diverges from your intent, when market conditions shift beyond what the agent was designed to handle, or when you simply want to pause and review. You should treat it as a standard safety tool, not only a last resort for catastrophic failures. If the agent begins repeating an unexpected pattern or if you notice a drawdown that exceeds your comfort level, the kill switch gives you a single action to halt everything and return control to you.

The best kill switches combine automatic triggers with manual controls. You might configure a drawdown limit that automatically flattens positions if the account balance drops by a threshold you define. You might also keep a manual override accessible from a separate device or interface. The key principle is that the agent cannot disable its own kill switch or override the automatic triggers. The API enforces these controls independently of the agent's logic. For a broader view of safe live deployment, see How to run an AI trading agent with real money, safely.

How do you plan exits before the agent starts?

Guardrails are not only about stopping bad behavior. They are also about enforcing good behavior. An exit plan tells the agent when to close a position, whether through a stop-loss, a time-based exit, or a take-profit level. If you do not define these rules in advance, the agent may hold a losing position indefinitely, hoping for a reversal that never comes, or it may exit a winning position too early based on an ambiguous prompt. Automated exits remove emotion from the decision and reduce the chance that you will need to use the kill switch.

The API allows you to attach exit instructions to individual orders or to set portfolio-level rules. You can define a maximum holding period, a maximum loss per trade, or a trailing exit that adjusts as the position moves in your favor. These rules are checked continuously by the API. If the agent tries to override or ignore them, the request is blocked. You can read more about structuring these rules in How to build your first automated exit plan and take-profit strategy. Setting exits before the first order is placed is one of the most effective ways to limit downside.

How do you test guardrails without risking real money?

Every beginner should start in paper trading mode. Paper trading simulates order execution across all five market types without moving real funds. It is the right environment to test whether your budget caps are actually enforced, whether the kill switch flattens positions as expected, and whether the agent respects scoped permissions. You should also test edge cases, such as what happens when the agent tries to exceed its position limit or access a restricted market. Observe how the agent behaves when it receives anomalous data or conflicting instructions. Paper trading exists for testing; live trading requires explicit owner authorization of a key, and that authorization should only happen after you have observed consistent, expected behavior.

When you do move to live trading, authorize only a small budget at first. Observe the agent for days, not hours. Check that the scoped key behaves exactly as it did in paper mode. Verify that the kill switch is accessible and that you know how to use it. Increase capital only after you have seen consistent behavior under real market conditions, including during volatile periods. Remember that trading can lose money, including everything, and small initial limits keep those losses contained while you learn how the agent behaves when real slippage and execution delays are present.

What should you review every week?

Guardrails decay if they are not reviewed. Markets change, your capital changes, and your agent's strategy may drift. Once a week, audit the agent's trade history against the scoped key permissions. Check whether the budget cap is still appropriate for your current account size and whether the position limits reflect your current risk tolerance. If you have added new markets or removed old ones, rotate the API key so the scope matches your present intent. A key that was scoped for a conservative stock strategy should not be reused for aggressive perps trading without a deliberate review and a new authorization step.

Also test the kill switch periodically. Revoke and reissue a key to confirm the process works and that you still have access to the owner controls. Review whether your exit plans triggered when they should have, or whether they failed to fire because of a subtle condition you did not notice during paper testing. These reviews take minutes and can prevent hours of damage. Safety is not a one-time setup; it is a recurring practice that adapts as your agent and your markets evolve. You can learn more about the underlying safety model in How a single API keeps AI trading agents safe by design.