Setup

Installation Methods

Global Installation

Install once, use everywhere. Skills are available in all Claude Code sessions:

git clone https://github.com/starlake-ai/starlake-skills.git ~/.claude/skills/starlake-skills

Project-Local Installation

Scope skills to a specific project. Useful when you want version-pinned skills:

cd your-starlake-project
git clone https://github.com/starlake-ai/starlake-skills.git .claude/skills/starlake-skills

Add to .gitignore if you don't want to commit the plugin:

.claude/skills/

Marketplace (Coming Soon)

claude plugin install starlake-skills

Starlake Project Structure

Starlake Skills expects the standard Starlake project layout:

your-project/
├── metadata/
│   ├── application.sl.yml          # Global config & connections
│   ├── env.sl.yml                  # Environment variables
│   ├── env.DEV.sl.yml              # Dev-specific overrides
│   ├── env.PROD.sl.yml             # Prod-specific overrides
│   ├── types/
│   │   └── default.sl.yml          # Data type definitions
│   ├── load/                       # Ingestion configurations
│   │   └── {domain}/
│   │       ├── _config.sl.yml      # Domain config
│   │       └── {table}.sl.yml      # Table schemas
│   ├── transform/                  # Transformation definitions
│   │   └── {domain}/
│   │       ├── {task}.sl.yml       # Task config
│   │       └── {task}.sql          # SQL logic
│   ├── extract/                    # Extraction configurations
│   ├── expectations/               # Data quality macros
│   ├── dags/                       # Orchestration templates
│   └── secure/                     # Security policies
├── datasets/                       # Data storage
│   ├── incoming/                   # Landing area
│   ├── pending/                    # Staging area
│   ├── accepted/                   # Validated data
│   ├── rejected/                   # Failed records
│   └── business/                   # Transformed data
└── starlake.sh                     # CLI wrapper script

Connection Configuration

Connections are defined in metadata/application.sl.yml:

application:
  connections:
    my-bigquery:
      type: BQ
      options:
        location: EU
        authType: APPLICATION_DEFAULT
    my-snowflake:
      type: JDBC
      options:
        url: "jdbc:snowflake://account.snowflakecomputing.com"
        user: "{{SNOWFLAKE_USER}}"
        password: "{{SNOWFLAKE_PASSWORD}}"
        warehouse: COMPUTE_WH
        db: ANALYTICS
    my-duckdb:
      type: JDBC
      options:
        url: "jdbc:duckdb:/path/to/database.db"
    my-postgres:
      type: JDBC
      options:
        url: "jdbc:postgresql://localhost:5432/mydb"
        user: "{{PG_USER}}"
        password: "{{PG_PASSWORD}}"

Connection Types

Type	Description	Use Case
BQ	Google BigQuery	Cloud data warehouse
JDBC	Generic SQL databases	Snowflake, PostgreSQL, DuckDB, Redshift
FS	File System	Local or cloud storage (GCS, S3)
ES	Elasticsearch	Search engine indexing
KAFKA	Apache Kafka	Event streaming

Environment Variables

Use env.sl.yml for variable substitution across your configuration:

env:
  SL_ROOT: "/path/to/project"
  SL_ENV: "DEV"
  SL_INCOMING: "{{SL_ROOT}}/datasets/incoming"
  SL_WAREHOUSE: "COMPUTE_WH"

Override per environment with env.{ENV}.sl.yml:

# env.PROD.sl.yml
env:
  SL_ENV: "PROD"
  SL_INCOMING: "gs://prod-bucket/incoming"
  SL_WAREHOUSE: "PROD_WH"

Verifying Your Setup

Run the validate skill to check your project:

You: /validate Check my entire Starlake project for configuration errors

This will verify:

• YAML schema compliance
• Connection references
• Domain and table configurations
• Type definitions
• Environment variable resolution

Next Steps

• Skills Catalog — Browse all available skills
• Connections — Detailed connection setup
• Warehouses — Warehouse-specific guides