looker-embed-demo

This skill enables agents to assist users in programmatically creating, updating, and managing Looker themes using the Looker API. Use this when you need to automate visual styling, implement brand-specific themes, or manage instance-wide default themes.

Detailed guidelines and mandatory workflows for localizing LookML models, views, explores, and dashboards, including string catalog creation and deployment via lkr-dev-cli.

Parent orchestrator skill for coordinating full-stack internationalization and localization across LookML models/dashboards and the React frontend application.

Comprehensive standards, UI design principles, tabbed report architecture, and automation patterns for creating and managing modern LookML dashboards using local LookML files and Looker MCP/CLI tools.

Analyzes a specific LookML dashboard (e.g., brand_lookup.dashboard.lookml), extracts all query elements and merge results, verifies them via run_inline_query(result="sql"), and self-heals missing LookML fields by iteratively adding best-guess calculations to local LookML views.

Standards, workflow rules, and helper patterns for managing LookML files in the Looker project using the `lkr-dev-cli` CLI tool, including full project and single-file push/pull synchronization and production deployment.

Guidelines and instructions for configuring Looker environment variables (.env), embed target IDs/routes (constants.ts), role permissions, and interacting with Looker MCP tools to fetch available dashboards, models, and explores.

Automated onboarding and provisioning skill that sets up the Looker Embed Demo project, database connection, LookML files via `lkr-dev-cli` CLI, LookML model configuration, brand user attribute, and instance embed settings on a new Looker instance.

Guidelines and architectural best practices for executing Looker SDK data queries, comparing static IDs (run_query) vs dynamic queries (run_inline_query), and choosing between json and json_detail result formats for HTML/currency consistency.

Step-by-step instructions and best practices for localizing the React frontend application using React Lingui v6, managing constant string catalogs, and executing required build commands.

Systematic workflow and cleanup skill for auditing React UI components, extracting hardcoded strings into relevant aliased config constant files, and triggering the localization extraction and compilation pipeline.

Guidelines and instructions for customizing application header titles, brand names, navigation breadcrumbs, and SVG or image logos in the Looker Embed Portal.

Parent orchestrator skill that invokes and coordinates all frontend customization workflows (branding, CSS theme tokens, Looker environment variables/constants, and opinionated Looker Brand Themes).

Guidelines and instructions for customizing the frontend CSS theme system, modifying design tokens (colors, typography, spacing, border radius, shadows, glassmorphism) in styles.css, and leveraging or extending core UI components.

Strict workflow and interactive loop guidelines for searching, diagnosing, implementing, and closing bug tracking system subtasks in partnership with the user.

Standards, architecture, and implementation for Just-in-Time access token refresh and initializing the official Looker Browser SDK with CustomEmbedSession.

Standards, workflows, and helper scripts for generating unit tests and mock data to test the Multi-Explore Experience Pattern (MEEP) in multiExploreUtils.ts.

Documentation for the Multi-Explore Experience Pattern (MEEP) which uses LookML field and Explore tags to manipulate field grouping, relabeling, timestamp linking, and exclusions in multi-explore environments.

Verifies and grants the mandatory Vertex AI User IAM role (roles/aiplatform.user) to the BigQuery Cloud Resource service account associated with Looker's database connection, enabling BigQuery ML generative AI functions (AI.*).

Overview of LookML field types (Dimension, Measure, Filter, Parameter) and the role of the `sql` parameter in each. Use this skill to choose the right field type for your data modeling needs.

Use this skill to create or modify LookML Views. Covers basic view definitions, sql_table_name, file organization, and patterns.

Guide on adding, modifying, or removing Looker user attributes (such as brand, locale) in both the frontend (state, constants, dialogs) and backend (Pydantic models, auth session endpoints) of this application.

Standards, architecture, and implementation details for Looker Embed Demo APIs (Token Reuse, Cookieless Embed, and Identity Middleware)

This skill enables agents to assist users in building streaming, data-driven agentic applications using the Looker Conversational Analytics (CA) API and Google ADK. Use this when you need to orchestrate multi-step data workflows with real-time feedback and conditional post-processing (e.g., visualization, analysis).

Use this skill when you need to build AI-powered chat interfaces (data agents) that query Looker data using natural language via the Gemini Data Analytics API.

Architectural pattern for performing direct browser-to-Looker API calls via CORS by using an application backend to delegate scoped authentication tokens.

This skill enables agents to assist users in implementing and troubleshooting interactive communication between a host application and an embedded Looker iframe using JavaScript events.

Guide to using LookML sets for grouping fields, controlling visibility, and managing drill paths.

This skill allows agents to assist users in setting up, implementing, and troubleshooting Looker SSO (signed) and Cookieless embedding using the Looker Embed SDK.

This skill enables agents to assist users in building custom, high-performance data experiences using Looker's React-based visualization components.