The Triggers (Getting the Workflow Started)
File / Folder Watch: The ultimate trigger for athletes. Landon uses this to watch a specific local storage directory on his device. The moment his high school team manager uploads raw .mp4 varsity game tape into the folder, his custom automation engine kicks off instantly.
Discord Message Received: Perfect for hanging out with teammates or gaming friends. This trigger activates the workflow directly via slash commands, specific text tags, or channel notifications inside a private friend server.
Telegram Message Received: Used for immediate, low-latency mobile control. Landon can text commands directly to his private bot while sitting on the bus or walking into the gym to check data states or run background scripts.
Instagram Activity: Activates automation tasks whenever his personal profile receives a new direct message, a comment, or a specific tag on an athletic clip.
🧠 AI & Agents Nodes (The Processing Core)
Agent (ai-agent): Landon drops this onto his canvas as his "Autonomous Predictive Coach." He writes its core prompt description to evaluate fast breaks, open lanes, and court spacing anomalies.
Skill (ai-skill): This is where Landon wires in specific rules and prompt formulas. For example, he inserts strict logic parameters here: "Quantify floor geometry, calculate the exact speed of pass transitions, and isolate individual defensive breakdowns."
Tool Call (ai-tool): Wraps his advanced OpenAI or Anthropic Claude connectors. It grants his active Agent node vision and multimodal capabilities to actually watch, analyze, and tag his athletic clips.
⚙️ Logic Nodes (Slicing the Data)
Split In Batches: Raw video streams contain a massive amount of data. This node cuts large information clusters down into tiny, uniform variables to prevent token overflow before pushing them to an AI model.
Computer: Running on the native Versian Node OS, Landon can use this node to drop in small, custom code snippets to handle simple mathematical equations, reformat file names, or sort play numbers automatically.
Delay / Wait: Crucial for balancing a student schedule. Landon programs his workflow to pause processing during school hours or active practices, releasing finished data summaries only after his homework window closes.
📡 The Connectors Marketplace (Sourcing and Storing)
Discord: Formats his automated game summaries into clean embed blocks, complete with timestamped notes, and pushes them straight into a private team channel to show his point-guard insights.
Canva / Figma: Landon can link his finished game metrics to a custom template canvas. The workflow uses this connection to automatically auto-generate stylish performance graphics or highlight cards that are formatted for social updates.
Google Slides: Compiles his weekly practice metrics and game statistics directly into an ongoing review deck, allowing him to easily track his performance over the course of the season.
Web Scraper: Landon uses this to keep tabs on his local high school sports conference website, scraping opposing team box scores, team standings, and roster statistics to prepare for his next matchup.
📊 Output Nodes (The Finish Line)
LED Indicator: A visual cue for his desktop setup. This node lights up a vibrant green indicator block on his home monitor interface, letting Landon know at a glance that his game review script executed successfully while he was away.
Dynamic Dashboard: Generates an interactive web view filled with customizable buttons, playback tracking graphs, and data fields, allowing Landon to easily review his personal athletic stats from any device.