Metabase

Migrates a project from Metabase static embedding to guest embeds (web components via embed.js). Use when the user wants to migrate/convert/switch/upgrade from static embedding to guest embeds, from signed embed iframes to web components, or replace /embed/ iframes with metabase-dashboard/metabase-question components.

Runs the Metabase semantic checker against a tree of Representation Format YAML files to verify that all references resolve — cross-entity references (collection_id, dashboard_id, parent_id, parameter source cards, snippet references, transform tags, etc.) and references to columns inside MBQL and native queries. Slow (≥1 min per run). Only use when the user explicitly asks to verify entity references or column references in MBQL/SQL queries; in most cases this runs as a CI step, not locally. Requires database metadata on disk (by default `.metadata/table_metadata.json`).

Understands the Metabase Representation Format — a YAML-based serialization format for Metabase content (collections, cards, dashboards, documents, segments, measures, snippets, transforms). Use when the user needs to create, edit, understand, or validate Metabase representation YAML files, or when working with Metabase serialization/deserialization (serdes). Covers entity schemas, MBQL and native queries, visualization settings, parameters, and folder structure.

First-time setup for the Metabase React SDK — instance detection, API key, dashboard discovery, JWT auth, SDK installation, and initial embedding code.

Upgrades a project's Metabase Modular embedding SDK (@metabase/embedding-sdk-react) or Modular embedding (embed.js) version. Use when the user wants to upgrade their Metabase modular embedding integration to a newer version.

Migrates a React project from Metabase Modular embedding (embed.js web components) to the Modular embedding SDK (@metabase/embedding-sdk-react). Use when the user wants to switch from embed.js web components to React SDK components (MetabaseProvider). This is not a version upgrade — it changes the embedding technology.

A spaced repetition learning coach for Metabase. Use this skill whenever the user wants to: learn Metabase, start a Metabase training session, do a Metabase review, practice Metabase concepts, check what they should study today, get quizzed on Metabase, run through active recall on BI tools, or follow a structured learning program for data analytics software. Trigger this skill even if the user just says "let's do my Metabase session", "quiz me on Metabase", or "what should I study today?" in a Metabase learning context.

Migrates a project from Metabase Full App / Interactive (iframe-based) embedding to Modular (web-component-based) embedding. Use when the user wants to replace Metabase iframes with Modular embedding web components.

Implements JWT SSO authentication for Metabase embedding in a project. Supports all embedding types that use SSO — Modular embedding (embed.js web components), Modular embedding SDK (@metabase/embedding-sdk-react), and Full app embedding (iframe-based). Creates the JWT signing endpoint, configures the frontend auth layer, and sets up group mappings. Use when the user wants to add SSO/JWT auth to their Metabase embedding, implement user identity for embedded analytics, set up JWT authentication for Metabase, or connect their app's authentication to Metabase embedding.

Understands the Metabase Database Metadata Format — a YAML-based on-disk representation of databases, tables, and fields synced from a Metabase instance. Use when the user needs to read, edit, or understand metadata files produced by `@metabase/database-metadata`, or when reasoning about a project's schema (columns, types, FK relationships) through the `.metadata/databases` folder.

Drive a Metabase instance from the terminal via the `mb` CLI. Authenticate with named profiles; inspect databases (list, get, full metadata rollup, schemas, tables in a schema) and trigger manual schema sync / field-values rescan; inspect tables, fields; list/get/create/update/archive cards (questions, models, metrics) and run them as JSON/CSV/XLSX; list/get/create/update dashboards and patch dashcards; list/get/create collections and traverse the hierarchy by id, entity_id, or "root"/"trash" (with items and recursive tree); list/get/create/update/archive native query snippets, segments, and measures; author/update/run transforms and schedule transform-jobs; read/update settings; search content (cards, dashboards, collections, transforms, metrics); manage Enterprise workspaces; git-sync to/from a git remote (status, dirty, import, export, branches, stash, add/remove a collection from sync). Use whenever the user wants to interact with a Metabase from the terminal — "log into metabase", "what profiles do I have", "list cards", "run card 42 as CSV", "create a transform", "list dashboards", "move a dashcard", "list collections", "what's in collection 4", "show the collection tree", "list snippets", "create a segment", "archive a measure", "search metabase for X", "spin up a workspace", "import the latest changes", "add a directory to git sync", "set a setting", "what schemas are in this database", "trigger a sync", "rescan field values", or anything hitting `mb <verb>`.

A Metabase AI-readiness coach, covering the *data groundwork* that makes AI answers trustworthy: modeling with Transforms, table and field metadata, the Glossary, saved Metrics, and marking canonical content. Use this skill whenever the user wants to check if their data is ready for AI, prep the underlying data for Metabot or the Metabase MCP server, work through an AI readiness checklist, or audit their data modeling/metadata/metrics before turning on AI features. Trigger it even if the user just says "is my data AI ready?", "let's get set up for Metabot", or "run the AI readiness checklist" in a Metabase context. **Not this skill** if the question is about controlling who may use AI, capping AI spend, restricting what Metabot can see, auditing AI usage, or passing a security review — that's `ai-governance-checklist`. Rough test: this skill is about whether the data is good enough; that one is about who gets to point AI at it.

A Metabase AI-governance coach, covering the *controls and rollout* side of AI: who may use Metabot, what it can see, what it costs, where the model runs, and the audit trail. Use this skill whenever the user wants to roll out AI analytics safely, control who can use Metabot or what it can see, set spend or token limits on AI, restrict Metabot's system prompt, audit AI usage, evaluate bring-your-own model or self-hosting options for AI, or prep for a security review of AI features. Trigger it even if the user just says "how do we control AI access", "can we limit what Metabot sees", "we need an AI security review", or "run the AI governance checklist" in a Metabase context. **Not this skill** if the question is about whether the underlying data is modeled, documented, and trustworthy enough for AI — Transforms, metadata, the Glossary, Metrics, the Library — that's `ai-readiness-checklist`. Rough test: this skill is about who gets to point AI at the data; that one is about whether the data is good enough.

Write TypeScript and JavaScript code following Metabase coding standards and best practices. Use when developing or refactoring TypeScript/JavaScript code.

Review TypeScript and JavaScript code changes for compliance with Metabase coding standards, style violations, and code quality issues. Use when reviewing pull requests or diffs containing TypeScript/JavaScript code.

Edit Metabase serdes YAML files (cards, dashboards, databases) with correct portable references and structural conventions. Use when modifying exported YAML content.

Export content from a running Metabase instance, validate with checkers, edit YAML, and import back. Use when the user wants to export, import, or run the full serdes round-trip workflow.

Drive Metabase's UI with the Playwright MCP browser tools (mcp__playwright__browser_*). Covers the snapshot/act/check pattern, Mantine component pitfalls (Menu race, Select/MultiSelect, the Escape-closes-modal trap, portal scoping), and Metabase-specific login flows. Use whenever a session needs to interact with the Metabase UI through Playwright MCP.

Run mutation testing on a Clojure namespace, generate tests to kill surviving mutations, and open draft PRs with Linear issue tracking.

Update or build a Metabase design-system component (frontend/src/metabase/ui — Chip, Badge, Alert, Switch, etc.) to match a Figma spec described in a Linear issue. Use when a ticket asks to restyle an existing `metabase/ui` component or implement a new one from Figma. Covers: checking out the issue, mapping the component (usage/blast radius for an existing one, or scaffolding a new one), building a Storybook showcase matrix (before styling for existing components, after for new ones), styling from exact Figma tokens while iterating with the user, and committing + migrating call sites LAST.

Scaffold a new Metabase data-app into the connected remote-sync repository's `data_apps/<app>/` directory from the `data-app-template`. Use when the user asks to start, create, scaffold, or set up a data-app from scratch.

Use when building, creating, or editing data apps that should query Metabase tables and metrics through generated schema files like metabase.data.ts or *.metabase.data.ts.

Add client-side routing (multiple pages) to an existing Metabase data-app project using the host-provided `DataAppRouter`, `DataAppLink`, and `useDataAppLocation` primitives. Use when the user has an existing data-app project and wants more than one page.

Use when a Metabase data app needs to trigger a write or mutation — submitting a form, updating a row, deleting an entry, running a saved action, or any "do something" interaction. Covers invoking an existing action via `useAction`, parameter typing, response handling, and the critical post-action refresh of any UI data the action may have changed.

Deciding where frontend code lives — tier model, move mechanics, extension points, side effects, naming, and the traps. Use when moving code between modules, carving new modules, fixing boundary violations, adding a barrel or an endpoint, or reviewing module-shape decisions.

Migrate Emotion styled-components to Mantine components with style props and CSS modules. Use when converting .styled.tsx files or removing @emotion imports from components.

Review Cypress E2E spec files for Metabase conventions, common gotchas, and flakiness/performance issues. Use when reviewing pull requests or diffs containing Cypress spec files in e2e/test/scenarios/.

Analyze React component source code to understand UI structure, then generate idiomatic Cypress E2E tests following Metabase conventions. Falls back to Playwright MCP browser exploration only when code reading and screenshot debugging are insufficient.

Run Cypress E2E tests, analyze failures including screenshots, and stress test for flakiness

Write documentation following Metabase's conversational, clear, and user-focused style. Use when creating or editing documentation files (markdown, MDX, etc.).

Review documentation changes for compliance with the Metabase writing style guide. Use when reviewing pull requests, files, or diffs containing documentation markdown files.

Guide Clojure and ClojureScript development using REPL-driven workflow, coding conventions, and best practices. Use when writing, developing, or refactoring Clojure/ClojureScript code.

Review Clojure and ClojureScript code changes for compliance with Metabase coding standards, style violations, and code quality issues. Use when reviewing pull requests or diffs containing Clojure/ClojureScript code.

Evaluate Clojure code via nREPL using clj-nrepl-eval. Use this when you need to test code, check if edited files compile, verify function behavior, or interact with a running REPL session.

Add product analytics events to track user interactions in the Metabase frontend

Add OpenTelemetry tracing spans to Clojure code following Metabase tracing conventions. Use when instrumenting backend code with trace coverage.

Efficiently add Malli schemas to API endpoints in the Metabase codebase with proper patterns, validation timing, and error handling