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genie-metadata-optimizer

Analyze evaluation failures and generate metadata patch proposals for Genie Spaces.

1|Updated Jan 22, 2026
Search Tags:#optimization#llm#metadata#semantic layer#genie#gepa#asi
One-click install
npx skills add https://github.com/prashsub/vibe_coding_lakehouse_starter_repo --skill genie-metadata-optimizer-prashsub
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: genie-metadata-optimizer
Source: https://github.com/prashsub/vibe_coding_lakehouse_starter_repo/tree/main/data_product_accelerator/skills/semantic-layer/genie-optimization-workers/03-genie-metadata-optimizer
Command: npx skills add https://github.com/prashsub/vibe_coding_lakehouse_starter_repo --skill genie-metadata-optimizer-prashsub

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses situations where evaluation scores are below target due to suboptimal Genie Space metadata, leading to inaccurate or inefficient AI responses.

Core Features & Use Cases

  • Metadata Optimization: Leverages L1 (ASI-grounded introspection) or L2 (GEPA) to propose and apply metadata changes.
  • Failure Analysis: Clusters evaluation failures to identify root causes and generate targeted patch proposals.
  • Use Case: After benchmarking, if your AI assistant's SQL generation accuracy is low, use this Skill to analyze the failures and automatically suggest improvements to table descriptions, column comments, or Genie instructions.

Quick Start

Use the genie-metadata-optimizer skill to analyze evaluation results and generate metadata patch proposals.

Frequently Asked Questions about genie-metadata-optimizer

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

FAQPage Schema
How do I optimize Genie Space metadata when evaluation scores are below target?▼

Optimize Genie Space metadata by analyzing evaluation failures and generating targeted patch proposals for table descriptions and column comments to improve AI SQL generation accuracy.

What is the best way to fix inaccurate AI responses caused by suboptimal Genie metadata?▼

Fix inaccurate AI responses by clustering evaluation failures to identify root causes in Genie metadata, then applying generated patch proposals to adjust instructions and column comments.

How does failure analysis improve Genie metadata patch proposals?▼

Failure analysis improves Genie metadata by clustering evaluation failures to map judge rationales directly to metadata fields, generating targeted patches and tracking blast radius for the Applier.

Can I use ASI-grounded introspection or GEPA to adjust Genie Space instructions?▼

Yes, leverage L1 ASI-grounded introspection or L2 GEPA to analyze benchmark failures and propose metadata changes to Genie Space instructions and table descriptions automatically.

Do I need benchmark evaluation results before generating Genie metadata patches?▼

Yes, benchmark evaluation results are required. The optimizer analyzes scenarios where evaluation scores are below target to generate control lever mappings and metadata patch proposals.

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