onboard-club

Automate club onboarding by providing club names to check against your database using fuzzy matching, generating onboarding tasks via /create-task for any venues not found. It extracts keywords to detect existing records and registers new clubs with metadata like name, city, and timezone.

Fuzzy matching checks existing club records by extracting keywords from input names and comparing them against database entries to detect similar or existing venues. This prevents duplicate onboarding tasks by identifying clubs already present in the database.

Yes, you need a live database connection, proper environment variables, and a configured scraper to onboard clubs. These prerequisites ensure club metadata, including name, city, state, timezone, and website, is accurately verified and created during the onboarding process.

The best way to create onboarding tasks for missing comedy clubs is to input venue names separated by commas. The system verifies them against your database, automatically generating tasks via /create-task for any clubs not found, then provides a summary of checked, skipped, and created items.

When onboarding new clubs, the scraper collects metadata including the club name, city, state, timezone, and website. This information is accurately created and registered in the database to ensure complete venue profiles for downstream task generation.

Club names are skipped during database verification because fuzzy matching and keyword extraction detected them as existing records. The system provides a summary of checked, skipped, and created items to support auditing and track onboarding progress accurately.