In plain terms: this is an AI assistant that works on a set schedule (e.g. daily). It uses AI to understand and generate content, so it handles judgement-style work, not just moving data. It connects to OpenRouter (LLM) and completes multi-step tasks for you automatically — the kind of work you'd otherwise hand to a virtual assistant.
20
Nodes
2
Integrations
18
Connections
Schedule
Trigger
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The real node graph exported from n8n — triggers (green), AI nodes (violet), services and logic — laid out as they run.
⚙️ How it works
Daily Content Trigger· scheduleTrigger
OpenRouter Chat Model· lmChatOpenRouter
Parse Script Output· outputParserStructured
OpenRouter Chat Model 2· lmChatOpenRouter
Prepare Final Data· set
Parse Video Prompts· outputParserStructured
Set Simple Storyline· set
AI Agent: Create Script from Storyline· agent
AI Agent: Generate Video Prompts from Script· agent
Split Scenes for Generation· code
Generate Video Clips· httpRequest
Wait for Video Generation· wait
Retrieve Generated Videos· httpRequest
Collect Videos for Stitching· code
💼 Business analysis
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Business use case
Deploys an autonomous AI agent that can reason over instructions, call tools, and take multi-step actions on behalf of a team — replacing repetitive knowledge work. It orchestrates OpenRouter (LLM), HTTP / REST API so a single natural-language request becomes a completed task.
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Market need
Businesses are racing to put AI agents to work but lack the engineering to wire models to their real tools and data. This delivers that wiring as a ready-to-run asset.
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Market value
Custom AI-agent builds are quoted at $3,000–$15,000+ by agencies, with managed retainers on top. As a productised template it commands premium one-time or subscription pricing.