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genie-optimization-applier

Apply metadata change proposals to Genie Spaces via API and repository files.

1|Updated Jan 22, 2026
Search Tags:#deployment#optimization#metadata#semantic layer#genie#dual persistence
One-click install
npx skills add https://github.com/prashsub/vibe_coding_lakehouse_starter_repo --skill genie-optimization-applier-prashsub
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: genie-optimization-applier
Source: https://github.com/prashsub/vibe_coding_lakehouse_starter_repo/tree/main/data_product_accelerator/skills/semantic-layer/genie-optimization-workers/04-genie-optimization-applier
Command: npx skills add https://github.com/prashsub/vibe_coding_lakehouse_starter_repo --skill genie-optimization-applier-prashsub

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates the application of metadata change proposals to Genie Spaces, ensuring consistency between the live API and repository files, and enabling robust deployment and rollback mechanisms.

Core Features & Use Cases

  • Dual Persistence: Applies changes to both the Genie API and repository files simultaneously.
  • Control Levers: Manages changes across six priority-ordered levers, from table/column metadata to Genie instructions.
  • Patch DSL: Utilizes a declarative Patch DSL for generating and executing changes with rollback capabilities.
  • Three-Phase Deployment: Integrates with Databricks bundles for validation, deployment, and Genie Space job execution.
  • Self-Healing: Supports self-healing deploy patterns with retries for robustness.
  • Use Case: Automatically apply optimization suggestions from an optimizer worker to a Genie Space, deploy the changes, and verify the results, ensuring the Genie Space remains optimized and consistent with its source code.

Quick Start

Apply the proposed metadata changes for space ID 'your-space-id' in the 'cost' domain.

Frequently Asked Questions about genie-optimization-applier

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I apply metadata changes to Genie Spaces and keep repository files in sync?▼

You can deploy optimized Genie Spaces using a three-phase deployment process via Databricks bundles. This handles validation, deployment, and Genie Space job execution automatically.

What is dual persistence when updating Genie Space semantic layer metadata?▼

Dual persistence is a deployment mechanism that applies metadata changes to both the Genie API and repository files simultaneously. It ensures live spaces and source code stay synchronized during optimization.

Can I automate Genie Space optimization deployments with rollback capabilities?▼

Yes, you can automate Genie Space deployments using a declarative Patch DSL that generates and executes changes. It includes built-in rollback capabilities to safely revert metadata updates if needed.

Does the Genie Space deployment process support self-healing retries?▼

Yes, Genie Space deployments support self-healing patterns with automated retries. This ensures temporary failures during the API or bundle deployment process do not permanently halt metadata updates.

How are Genie Space metadata optimization changes prioritized?▼

Genie Space metadata changes are managed through six priority-ordered control levers. This structured approach handles updates ranging from table and column metadata down to Genie instructions.

What's the best way to deploy optimized Genie Spaces using Databricks bundles?▼

The best way to deploy optimized Genie Spaces is a three-phase integration using Databricks bundles. It handles validation, deployment, and job execution while preserving template variables and sorting configurations.

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