metabase-learning

A Metabase skill that understands the YAML-based on-disk representation of database metadata (databases, tables, fields) synced from a Metabase instance. Enables reading, editing, and reasoning about schema structure, column types, and FK relationships through diff-friendly YAML files.

A collection of agent skills for working with Metabase, covering the mb CLI for terminal-driven operations, database metadata exploration, embedding SSO implementation, and full-app to modular embedding migration. Built for Claude Code with compatibility for other AI coding agents.

A skill for understanding and working with the Metabase Representation Format, a YAML-based serialization format for Metabase content including collections, cards, dashboards, documents, segments, and more. Covers entity schemas, MBQL/native queries, visualization settings, and validation.

Validates Metabase Representation Format YAML files for referential integrity by checking cross-entity references and compiling MBQL queries to SQL against database metadata. Runs after schema validation to ensure collection IDs, dashboard references, and column references all resolve correctly.

Upgrades a project's Metabase modular embedding SDK or embed.js to a newer version, handling migration of embedding integration code and configuration changes.

Implements JWT SSO authentication for Metabase embedding including modular embedding, SDK integration, and full app iframe-based embedding with user identity and group mappings.

A migration skill that converts Metabase full-app/interactive iframe-based embedding to modular web-component-based embedding, handling iframe replacement with components like metabase-question and metabase-dashboard, embed.js setup, and SSO endpoint modifications.

Migrates Metabase static embedding (signed iframe approach) to guest embedding using web components via embed.js. Follows a structured 6-step workflow covering version detection, project scanning, embed mapping, code migration, and validation.

Agent skill for Metabase that helps perform complex embedding migrations and upgrades, explore data models, and create Metabase content automatically using AI coding agents.

Guides the first-time setup of the Metabase React SDK for embedding dashboards, covering instance detection, API key configuration, dashboard discovery, JWT authentication, SDK installation, and initial embedding code generation. Provides a step-by-step interactive workflow that validates prerequisites before proceeding.