Detect human vs AI text using stylometric metrics and multi‑agent LLM debate
Ready for 3.0What this workflow does
This AI workflow has 22 nodes and runs when a chat message arrives (plus 1 other trigger). Along the way it connects Groq Chat Model, OpenAI Chat Model, Anthropic Chat Model and Google Gemini Chat Model.
How it runs
Trigger: When a chat message arrives (plus 1 other trigger).
- Load Fingerprint List (Data table): get
- Check Existing Words (Data table): get
- Extract Stylometric Metrics (Code): runs custom JavaScript code
- Format Existing List (Code): runs custom JavaScript code
- Agent Orchestrator (Chat): uses Chat
- Find New Words (Basic LLM Chain): sends a prompt to an LLM, with model: LLM - Generator
- Agent 1 - The Scanner (AI Agent): runs an AI agent, with model: LLM Scanner
- Split into Rows (Code): runs custom JavaScript code
- Package Scanner Output (Code): runs custom JavaScript code
- Save New Fingerprints (Data table): uses Data table
…plus 6 more steps. See the full node list below.
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (11)
- Code
n8n-nodes-base.code - AI Agent
@n8n/n8n-nodes-langchain.agent - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Schedule Trigger
n8n-nodes-base.scheduleTrigger - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - Chat
@n8n/n8n-nodes-langchain.chat - Data table
n8n-nodes-base.dataTable - Groq Chat Model
@n8n/n8n-nodes-langchain.lmChatGroq - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Anthropic Chat Model
@n8n/n8n-nodes-langchain.lmChatAnthropic - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini
From the author
Stop guessing if text came from ChatGPT. Let three AI agents argue about it using forensic data. Paste any text and get a verdict on whether it was written by a human, AI, or a hybrid mix. Instead of trusting one black-box score, this workflow runs your text…