Does content filtering add latency to responses?

Content filtering adds a small amount of latency, typically under 200 milliseconds. Input filtering runs before the model, and output filtering runs after. The combined overhead is minimal compared to model inference time.

Can I disable filtering for trusted users?

Yes. You can configure user tiers where trusted or internal users bypass certain filter categories. However, output filtering should remain active for all users to prevent the agent from generating harmful content regardless of who is asking.

What is the difference between content filtering and prompt engineering?

Prompt engineering sets the agent's intended behavior through instructions. Content filtering enforces boundaries by checking actual inputs and outputs against rules. Both are necessary: prompts guide the model, and filters catch the cases where the model deviates from those guidelines.

Security

Content Filtering: Safety and Moderation

Configure content filtering rules that prevent your OpenClaw agent from generating or accepting harmful, inappropriate, or off-topic content.

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What You Will Get

By the end of this guide, your OpenClaw agent will have content filtering rules that block harmful inputs, prevent inappropriate outputs, and maintain a safe, professional conversation environment. Both user messages and agent responses will be screened against your moderation policies.

Content filtering is essential for any agent that interacts with the public or operates in a regulated environment. Without filters, users can manipulate the agent into generating harmful content, and the agent may occasionally produce inappropriate responses on its own.

You will configure input filters, output filters, topic restrictions, jailbreak detection, and escalation procedures. The result is an agent that stays within the boundaries you define, protects your brand, and keeps users safe.

Step-by-Step Setup

Follow these steps to configure content filtering.

Enable the Content Filter Module

Open your agent's Security settings and navigate to Content Filtering. Enable the module to activate both input and output filtering. The module runs a lightweight check on every message before it reaches the model and before the model's response reaches the user.

Configure Input Filters

Set up rules for incoming user messages. Enable filters for harmful content categories like violence, hate speech, personal information, and explicit content. Each category can be set to block (reject the message), warn (flag but allow), or log (record without action). Choose the appropriate response for each based on your use case.

Configure Output Filters

Set up rules for the agent's responses. Even with a well-crafted system prompt, the model can occasionally generate inappropriate content. Output filters catch these cases and either redact the problematic content, regenerate the response, or return a safe fallback message.

Define Topic Restrictions

Specify topics the agent should not discuss, such as competitors, legal advice, medical diagnoses, or political opinions. Add these as restricted topics in the content filter configuration. When the agent detects a restricted topic, it responds with a predefined redirect message like 'I am not able to help with that topic, but here is where you can find more information.'

Enable Jailbreak Detection

Turn on jailbreak detection to identify attempts to manipulate the agent into bypassing its instructions. The detector recognizes common jailbreak patterns like role-play prompts, instruction overrides, and prompt injection. Detected attempts are blocked and logged for review.

Configure Escalation Procedures

Define what happens when content filtering triggers. For blocked messages, configure a polite rejection message. For flagged content that is allowed through, configure a notification to a human moderator. For repeat offenders, consider temporary rate limiting or blocking.

Test with Adversarial Inputs

Test your filters with a range of problematic inputs: obvious harmful content, subtle manipulation attempts, edge cases that are close to but not quite harmful, and legitimate messages that might false-positive. Tune your filter sensitivity based on the results.

Tips and Best Practices

Balance Safety with Usability

Overly aggressive filters block legitimate messages and frustrate users. Start with moderate sensitivity and tighten only if you see harmful content getting through. Review false positives weekly and add exceptions for commonly blocked legitimate phrases.

Keep a Moderation Queue

Configure a moderation queue for flagged messages that are not clearly harmful. A human moderator can review these and decide whether to allow or block. This catches edge cases that automated filters struggle with.

Update Filters Regularly

New manipulation techniques emerge constantly. Review and update your jailbreak detection patterns and filter rules quarterly. The RunTheAgent filter database receives updates automatically, but custom rules need manual maintenance.

Log All Filter Actions

Log every filter trigger with the original message, the action taken, and the category. This data helps you understand what your users are trying to do, improve your filters, and demonstrate moderation efforts during compliance audits.

Frequently Asked Questions

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