Detect NSE options anomalies with Supabase, OpenAI, Google Sheets and Gmail

Quick overview This workflow runs every 30 minutes to scan an NSE options watchlist from Google Sheets, fetch option chain data via HTTP, compare it with historical snapshots in Supabase, generate an OpenAI interpretation for anomalies, log results to Google Sheets, and send a Gmail digest alert. How it works 1. Runs every 30 minutes on a schedule. 2. Reads a watchlist from Google Sheets and keeps only symbols marked as enabled, along with their scan settings. 3. Requests the latest option chain for each symbol from the configured HTTP endpoint and normalizes the returned contracts into a consistent structure. 4. Pulls historical option snapshot data for each symbol from Supabase and calculates volume ratio, open-interest ratio, and a z-score to flag anomalous contracts. 5. For anomalous contracts, saves the full option snapshot to Supabase and asks OpenAI to generate a concise plain-text interpretation with observation, possible interpretation, and a risk note. 6. Stores the AI-enriched anomaly record in a Supabase anomalies table, appends the anomaly to a Google Sheets log, and builds a single text digest. 7. Sends the digest email through Gmail to the configured recipient. Setup 1. Connect Google Sheets credentials and update the spreadsheet ID and sheet tabs for the watchlist and anomaly log. 2. Configure the HTTP request URL to point to your NSE option chain data source and ensure it returns the expected contract fields (symbol, expiry, strike, optiontype, ltp, volume, openinterest, changeinoi, iv, underlyingprice, capturedat, source). 3. Connect Supabase credentials and create/configure the required tables (optionsnapshots and optionanomalies) with columns matching the fields the workflow writes. 4. Add an OpenAI API credential (and adjust the model, if needed) for generating the anomaly interpretation. 5. Connect a Gmail OAuth credential and set the recipient email address in the email-sending step. Additional info Use Case Examples 1. NSE Options Activity Monitoring Automatically monitor configured NSE symbols and identify contracts showing unusual volume, open interest, or statistical activity. 2. Unusual Volume Detection Identify contracts where current volume is significantly higher than the configured historical baseline. 3. Open Interest Monitoring Identify option contracts where current open interest exceeds the configured anomaly threshold. 4. Statistical Anomaly Monitoring Use the calculated z score to identify option contracts whose activity differs significantly from the calculated historical pattern. 5. Automated Market Activity Reporting Store detected anomalies in Supabase, maintain a Google Sheets log, generate AI explanations, and receive a consolidated Gmail report. There can be many more use cases based on the available market data and the additional calculations or notification channels added to the workflow. Troubleshooting Guide | Issue | Possible Cause | Solution | | -------------------------------------- | ------------------------------------------------------------------------ | ------------------------------------------------------------------------------------ | | No symbols are processed | Watchlist entries are disabled | Check the enabled column and set the required symbols to true | | Watchlist data is not loading | Google Sheets credentials or sheet configuration is incorrect | Verify the Google Sheets credential, document, worksheet, and column names | | HTTP Request returns no contracts | The configured endpoint is unavailable or its response structure changed | Test the endpoint and verify that it returns the expected data collection | | Contract fields are empty | The HTTP response does not match the expected structure | Compare the response fields with the fields required by Normalize Option Contracts | | Historical data is missing | Supabase table has insufficient records | Verify that optionsnapshots contains historical records for the scanned symbol | | No anomalies are detected | C