Looker Demo Creator (demo-create)

Automated, deterministic orchestrator for creating end-to-end Looker demos, synthetic BigQuery datasets, LookML semantic models, and Embedded Analytics portals.

Overview

demo-create is a developer and AI agent tool that unifies the end-to-end Looker demo creation lifecycle into a single workflow:

1. Pre-flight & Environment Audit (pre-check): Verifies active GCP/ADC accounts, installs/patches global MCP tools (data-designer, bigquery, knowledge-catalog), checks Looker authentication (OAuth / API keys), and organizes agent skills (including lkr-code-mode) into intent-based subfolders.
2. Dataset Decision & Synthesis: Automatically checks for existing BigQuery datasets, enables data augmentation or green-field relational schema generation, and validates referential integrity.
3. BigQuery Loading: Creates datasets and partitioned/clustered tables in BigQuery.
4. LookML Generation & Direct Code-Mode Deployment: Autogenerates production-ready views, explores, and executive dashboards, provisioning and deploying them directly to the Looker instance using lkr-dev-cli code-mode without requiring an MCP server.
5. Embedded Portal Scaffolding: Clones and configures a clean, dedicated looker-embed-demo workspace for external client demos.

Quickstart & Installation

1. Install as a Persistent CLI Tool (uv tool - Recommended)

To make demo-create, looker-demo-cli, AND lkr (lkr-dev-cli) globally available on your shell's PATH in a persistent, isolated environment:

# Install the published package globally
uv tool install looker-demo-cli

# Now all tools execute directly with zero startup latency and pre-pinned dependencies:
demo-create pre-check --fix
lkr auth list

To update to the latest version at any time:

uv tool upgrade looker-demo-cli

2. Run Ephemerally with uvx (Zero-Install Alternative)

You can also execute the CLI on-demand in an ephemeral cache without pre-installing:

# Run pre-flight audit and auto-fix MCP / skills
uvx looker-demo-cli pre-check --fix

# Or invoke the demo-create binary explicitly
uvx --from looker-demo-cli demo-create pre-check --fix

# Run end-to-end interactive demo creator
uvx looker-demo-cli run --project=retail_analytics --scope=internal

3. Workspace Virtual Environment & Script Runner

To eliminate missing dependency errors across agent scratch scripts or data synthesis pipelines:

# Initialize a local .venv with all demo packages pre-installed:
demo-create env init
source .venv/bin/activate

# Execute ad-hoc scratch scripts using the CLI's bundled Python environment:
demo-create run-script scratch/generate_data.py

# Run one-off Python commands in the demo environment:
demo-create python -c "import pandas, pyarrow, google.cloud.bigquery; print('Ready!')"

4. Running from Local Source or Git (Development)

If developing locally or testing from a Git repository:

Run directly from local source directory:

uvx --from . demo-create pre-check --fix

Run directly from Git:

uvx --from git+https://github.com/lkrdev/looker-demo-cli.git demo-create pre-check --fix

Local Editable Installation:

cd ~/looker-demo-cli
demo-create env init
source .venv/bin/activate
uv pip install -e .

Commands & Usage

1. Environment & Skill Audit (pre-check)

# Run visual audit of GCP credentials, MCP tools, and intent skills
demo-create pre-check

# Automatically install missing MCP configs and symlink skills into intent subfolders
demo-create pre-check --fix

# Emit raw JSON report for programmatic agent consumption
demo-create pre-check --json

2. End-to-End Demo Creation (run)

# Interactive wizard
demo-create run --project=retail_insights --scope=internal

# Non-interactive / Agent Mode
demo-create run \
  --project=logistics_analytics \
  --scope=external \
  --gcp-project=my-analytics-project \
  --gcp-account=user@example.com \
  --agent-mode

Intent-Based Skill Organization

When you run demo-create pre-check --fix, skills are automatically pulled from remote repositories and organized into ~/.gemini/config/skills/:

~/.gemini/config/skills/
├── data-design/
│   ├── data-designer/
│   ├── data-designer-architect/
│   ├── data-designer-engineer/
│   ├── data-designer-evaluator/
│   └── vertex-ai/
├── lookml/
│   ├── lkr-code-mode/
│   ├── repo-lookml/
│   ├── lookml-model/
│   ├── lookml-explore/
│   ├── lookml-view/
│   ├── lookml-dashboard/
│   ├── lookml-dashboard-to-query/
│   └── embed-themes/
└── embed-portal/
    ├── looker-demo-orchestrator/
    ├── setup-embed-demo/
    ├── customize-frontend/
    ├── customize-frontend-branding/
    ├── customize-frontend-theme/
    └── sso-embed/

This guarantees that any Jetski agent in any directory can discover and execute Looker demo workflows.