Guides AI agents through Looker onboarding and LookML development: authenticating the Looker CLI, connecting BigQuery sources, generating views, models, explores, dashboards, and applying security grants, testing, and best practices for maintainable Looker projects.
Looker Developer Onboarding: Step 3. Authenticates the Looker CLI using OAuth. Only execute this after Step 2 (CLI Verification using `installing-looker-cli`).
Looker Developer Onboarding: Step 4. Creates a database connection in Looker to Google BigQuery. Only execute this after Step 3 (CLI Authentication using `authenticating-looker-cli`).
Looker Developer Onboarding: Step 7 (Final Step). Creates a LookML dashboard in the project, imports it as a user-defined dashboard (UDD) in Looker, and iteratively refines it based on user feedback by syncing changes. Only execute this after Step 6 (Model Setup using `creating-lookml-model`).
Looker Developer Onboarding: Step 6. Creates LookML views and models based on the user's goals, maps model connections, validates LookML, and runs verification queries. Only execute this after Step 5 (Project Setup using `setting-up-looker-project`).
Looker Developer Onboarding: Step 1. Guides the agent to explore BigQuery data and define the onboarding goal. This is the first active step, to be executed immediately after reading the parent orchestrator `looker-developer-onboarding`.
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Sign in to claimnpx claudepluginhub looker-open-source/looker-skillsBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
This repository contains a collection of "skills" designed to assist AI agents and developers in writing high-quality, standardized LookML code and guiding them through Looker onboarding. Each skill encapsulates specific instructions, best practices, and examples for different aspects of Looker development.
To use these skills in your own projects—especially to enhance AI assistants like Gemini, Cursor, Antigravity, or Claude Code—we recommend adding this repository to your project.
The skills CLI is a tool used to install and manage specialized instructions (skills) for AI agents in your workspace. To install these LookML skills in your project, use npx skills add.
npx skills add looker-open-source/looker-skills
These skills provide specific instructions for creating and modifying LookML objects.
access_filter, sql_always_where, and UNNESTing arrays.sql_table_name, and file organization (Standard, Extended, Refined).sql parameter in each.access_grant and required_access_grants for row-level security.These skills guide new Looker developers and agents through database exploration, CLI setup, project configuration, LookML modeling, and dashboard creation.
Connect to Looker and interact with your data using LookML.
Build, validate, and query Sidemantic semantic models, and generate analytics webapps from them. Ships the modeler and webapp-builder skills.
Explore, query, model, embed, and manage Omni Analytics through the REST API and embed SDK. Includes 9 skills, 3 specialized agents, and 3 context rules for model exploration, querying, model building, content browsing, content building, embedding, AI optimization, AI eval, and administration.
Semantic SQL compiler — compile .view.yml schema definitions into dialect-specific SQL. Unix-philosophy CLI designed as a tool-use interface for LLMs.
Skills for analytics engineering with dbt — building models, writing tests, querying the semantic layer, troubleshooting jobs, and more.
Editorial "Data & Analytics" bundle for Claude Code from Antigravity Awesome Skills.