Mod Queue Summarizer

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Inspiration

Moderator Copilot (mod-copilot-nb) is a Devvit-powered moderation assistant that helps Reddit moderators efficiently review and act on content in the mod queue. Instead of manually reviewing every report or thread, the app groups related activity, summarizes what’s happening, and provides explainable moderation suggestions.

The goal is to reduce moderation overhead while keeping moderators fully in control of all actions.

What it does

Summarizes mod queues, clusters similar reports, and suggests moderation actions with clear reasoning.

Core Features

1. Smart Mod Queue Summarization

• Automatically clusters similar posts and reports
• spam waves
• repeated rule violations
• coordinated behavior
• Generates concise summaries explaining activity patterns
• Reduces queue noise and helps moderators prioritize quickly

2. Action Suggestions with Reasoning

• Recommends moderation actions such as:
• remove
• approve
• ignore
• lock
• Maps decisions to subreddit-specific rules
• Provides transparent reasoning to maintain moderator trust

3. Context-Aware Reply Generation

• Drafts human-like moderator responses
• Explains rule violations clearly and respectfully
• Helps maintain a consistent moderation tone without sounding robotic

4. Intent Classification

• Detects whether content appears to be:
• good-faith discussion
• trolling
• harassment
• spam
• Helps moderators focus attention on high-value interactions

5. Risk & Escalation Detection

• Flags threads likely to escalate due to:
• brigading
• hostility spikes
• rapid toxic engagement
• Enables early moderator intervention before conflicts grow

How we built it

The moderator system was built as an AI-assisted moderation copilot using a modular agent architecture, where specialized pipelines handle summarization, classification, risk detection, actions, and reply generation while integrating Reddit APIs, embeddings, and a dashboard interface to help moderators review and manage community discussions efficiently.

Built using Reddit API, embeddings for similarity search, RAG pipeline, and an LLM for summarization and decision support.

How Moderators Use It

Moderators access the tool directly from the subreddit menu using: “Open Moderator Copilot” The application analyzes the current moderation queue and presents:

• grouped content clusters
• activity summaries
• suggested actions with explanations
• optional moderator reply drafts

Moderators can always accept, modify, or ignore recommendations.

Design Principles

• Assist moderators — never replace them
• Provide transparent and explainable reasoning
• Adapt to subreddit-specific rules and culture
• Reduce cognitive load and moderator burnout
• Preserve human judgment and accountability

Project Impact

Target Communities & Impact

r/AskReddit

• Extremely high comment volume creates heavy moderation overhead
• Moderator Copilot reduces triage time by clustering related issues
• Helps moderators quickly identify priority discussions

r/technology

• Frequent rule violations and heated debates
• Risk detection enables early intervention in escalating threads
• Helps reduce toxic engagement before it spreads

r/smallbusiness

• Mix of legitimate questions and promotional spam
• Intent classification improves prioritization of good-faith participation
• Helps moderators focus on community-building interactions

Challenges we ran into

Handling noisy, unstructured Reddit data and ensuring accurate, context-aware moderation suggestions.

Accomplishments that we're proud of

Built an AI-powered moderation copilot that reduces moderator workload through intelligent triage, risk detection, and subreddit-aware decision support while preserving human oversight.

What we learned

Effective moderation tools must prioritize transparency, context, and human-in-the-loop decision making.

What's next for Mod Queue Summarizer

Add real-time streaming, subreddit customization, better risk scoring, and deeper mod workflow integrations.

Built With

• and-aws-(s3
• ec2)
• embeddings
• fastapi
• lambda
• langchain/langgraph
• openai-llm-apis
• postgresql
• python
• reddit
• redis
• vector-databases-(pinecone/pgvector)