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Overview

Rules define content moderation criteria in PixelPatrol. Each rule evaluates specific aspects of submitted content, and rules work together within Rule Groups to provide comprehensive content filtering. Important: All rule management is done through the dashboard interface - no API access is available for creating, editing, or managing rules.

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How Rules Work

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Rule Group Logic

Within each rule group, ALL rules must pass for content to be approved. If any single rule fails, the content is flagged for moderation. This ensures comprehensive content filtering without compromise. Example: A “Profile Photos” rule group with 3 rules:
  • ✅ No explicit content (passes)
  • ✅ Must have clear face (passes)
  • ❌ No children in photos (fails)
  • Result: Content is rejected because one rule failed

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Rule Types

Requirements

Content must satisfy this condition:
  • Must have clear face
  • Must be high quality
  • Must match profile

Prohibitions

Content must avoid this condition:
  • No explicit content
  • No violence/weapons
  • No children

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Available Rule Templates

PixelPatrol provides 16 pre-built rule templates optimized for different moderation needs:

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Content Safety

  • Explicit Content - Blocks NSFW/adult content
  • Violence/Weapons - Prevents violent imagery
  • Drugs/Alcohol - Filters substance-related content
  • Offensive Gestures/Symbols - Blocks inappropriate symbols

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Image Quality

  • No Clear/Focused Face - Ensures face visibility
  • Unclear/Blurry Image - Maintains quality standards
  • Fake/Generated Image - Detects AI-generated content
  • Screenshot Detected - Prevents screenshot uploads

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Content Compliance

  • Contains Children - Protects child safety
  • Multiple Focal Points - Ensures single-person focus
  • Celebrity Detected - Prevents celebrity photos
  • Excessive Text - Limits text overlays

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Privacy & Identity

  • Consent/Privacy Violation - Protects user privacy
  • Offensive Text/Images - Blocks inappropriate overlays
  • Gender Mismatch - Validates gender matches profile (requires advanced parameters)

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Custom Rules

Create completely custom rules for specific business requirements not covered by templates.

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Rule Configuration

Each rule can be configured with:
  • Name: Descriptive identifier for the rule
  • Description: Explanation of what the rule does
  • Evaluation Type: Requirement or Prohibition
  • Confidence Threshold: How confident AI must be (50%-100%)
  • Active Status: Enable/disable without deleting
  • Advanced Parameters: Additional metadata requirements

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Confidence Thresholds

Set how confident the AI must be in its evaluation:
  • High (85-95%): Fewer false positives, more false negatives
  • Medium (70-85%): Balanced approach (recommended starting point)
  • Low (50-70%): More false positives, fewer false negatives

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Advanced Parameters

Some rule templates support advanced parameters that use metadata from your media submissions for more precise moderation.

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Gender Matching Example

The “Gender Mismatch” rule requires gender information from media metadata: 
{
  "type": "object",
  "required": [
    "gender"
  ],
  "properties": {
    "gender": {
      "type": "string",
      "description": "User's stated gender (e.g., male, female, non-binary)"
    }
  }
}
The AI validates that the photo matches the stated gender, helping ensure profile authenticity.

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Industry Use Cases

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Social Media Platform

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E-commerce Platform

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Dating Application

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Creating Rules via Dashboard

  1. Navigate to Rule Groups: Sites → [Your Site] → Rule Groups
  2. Select Rule Group: Choose the group to add rules to
  3. Click “Add Rule”: Opens the rule creation dialog
  4. Select Template: Choose from pre-built templates or “Custom”
  5. Configure Settings:
    • Set evaluation type (requirement/prohibition)
    • Adjust confidence threshold
    • Add any advanced parameters
  6. Test & Save: Use test interface to validate before saving

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Best Practices

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Rule Organization

  • Group by purpose: Keep related rules together
  • Limit group size: 3-7 rules per group for optimal performance
  • Name clearly: Use descriptive names that explain the rule’s purpose

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Threshold Tuning

  • Start at 85%: Begin with higher confidence and adjust down if needed
  • Test with real content: Use actual examples from your platform
  • Monitor false positives: Review flagged content regularly
  • Adjust gradually: Make small threshold changes (5-10%)

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Advanced Parameters

  • Validate availability: Ensure your app provides required metadata
  • Handle missing data: Consider fallback behavior
  • Privacy first: Only collect necessary information
  • Document requirements: Clearly communicate metadata needs

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Monitoring Performance

Track rule effectiveness through the dashboard:
  • Trigger Frequency: Which rules activate most often
  • Confidence Distribution: How confident AI is in decisions
  • False Positive Rate: Rules that may need adjustment
  • Processing Time: Rule evaluation performance
Pro tip: Review your moderation logs weekly to identify patterns and optimize rule configurations. Rules that trigger too frequently or rarely may need threshold adjustments.

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Limitations

  • No composite rules with OR logic - all rules must pass
  • No variables or dynamic values in rule configuration
  • No API access - all management through dashboard only
  • Rules evaluate independently - no dependencies between rules