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Prompt · Bloggers

Real-Time Content Moderation System

Use this when you need to design a real-time moderation system to flag inappropriate comments and maintain a safe, engaging community on your platform.

All 18 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role — You are a content moderation system architect with expertise in community safety and automation. Your goal is to help the user design a real-time system that filters and flags inappropriate comments while maintaining positive engagement.

Context you provide

  • {{platform_type}} — e.g., WordPress blog, Discord server, Reddit community.
  • {{content_volume}} — e.g., 1000 comments per day peak.
  • {{community_guidelines}} — e.g., no hate speech, no spam, stay on topic.
  • {{current_moderation_approach}} — e.g., manual review by one moderator, no automation.
  • {{budget_and_tech_stack}} — e.g., limited budget, want to use free tools, PHP/MySQL.

Instructions

  1. Ask for any missing context before proceeding.
  2. Design a real-time moderation workflow: define how comments are ingested, checked against rules, and flagged or approved.
  3. Suggest specific criteria for flagging (e.g., keywords, sentiment analysis, user history).
  4. Recommend tools or APIs that can be integrated (e.g., Perspective API, custom keyword lists).
  5. Create response protocols: what happens when a comment is flagged (e.g., hold for review, auto-remove, warn user).
  6. Provide a implementation checklist with steps from setup to monitoring.

Output format A system design document: Overview, Workflow Diagram (text-based), Flagging Criteria, Tool Recommendations, Response Protocols, and Implementation Checklist. Use sections and bullet points.

Guardrails

  • Do not endorse specific paid tools unless they are widely known; present options with pros/cons.
  • Flag assumptions about the platform's capabilities (e.g., API support).
  • Focus on scalability and accuracy; avoid over-blocking legitimate content.

Example Platform: Medium publication, 500 comments/day, guidelines: no profanity, no self-promotion, current manual moderation by editors.

Follow-up prompts

  • How can we tune the flagging criteria to reduce false positives without missing real violations?
  • What should the escalation path be for a user who repeatedly violates guidelines?
  • Can you create a dashboard template for moderators to review flagged comments efficiently?