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🛡️ AI Moderator

For an overview of all available workflows, see the main README.

Automatically detect spam, link spam, and AI-generated content in GitHub issues, comments, and pull requests

The AI Moderator workflow helps maintain quality discussions and protect your repository from malicious or low-quality contributions by automatically moderating incoming content.

Installation

# Install the 'gh aw' extension
gh extension install github/gh-aw

# Add the workflow to your repository
gh aw add-wizard githubnext/agentics/ai-moderator

This walks you through adding the workflow to your repository.

How It Works

graph LR
    A[New Issue/PR/Comment] --> B[Analyze Content]
    B --> C{Spam or<br/>AI-Generated?}
    C -->|Spam| D[Add Label & Hide]
    C -->|AI-Generated| E[Add ai-generated Label]
    C -->|Clean| F[Add ai-inspected Label]
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The workflow reads new issues, comments, and pull request diffs, then applies appropriate labels (spam, link-spam, ai-generated, or ai-inspected). It can hide comments detected as spam. Requires issues: write and pull-requests: write permissions for full functionality.

Usage

This workflow triggers automatically when issues, comments, or pull requests are created—you cannot start it manually.

Configuration

The workflow works out of the box with sensible defaults. You can customize:

  • Labels to apply for different detection types
  • User roles that are skipped (defaults to admins, maintainers, write access, and triage)
  • Bots to skip (defaults to github-actions and copilot)
  • Rate limiting settings
  • Detection criteria and thresholds

After editing run gh aw compile to update the workflow and commit all changes to the default branch.

Human in the Loop

  • Review labels applied to ensure accurate spam detection
  • Monitor for false positives and adjust detection criteria if needed
  • Override moderation decisions when the AI makes mistakes
  • Unhide legitimate content if necessary