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project-planning

Generate multi-phase Databricks project plans with YAML manifests.

1|Updated Jan 22, 2026
Search Tags:#project planning#agent framework#databricks#data platform#manifest generation#genie spaces
One-click install
npx skills add https://github.com/prashsub/vibe_coding_lakehouse_starter_repo --skill project-planning-prashsub
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: project-planning
Source: https://github.com/prashsub/vibe_coding_lakehouse_starter_repo/tree/main/data_product_accelerator/skills/planning/00-project-planning
Command: npx skills add https://github.com/prashsub/vibe_coding_lakehouse_starter_repo --skill project-planning-prashsub

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires databricks-expert-agent, naming-tagging-standards, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill streamlines the creation of comprehensive, multi-phase project plans for Databricks data platform solutions, ensuring alignment with architectural best practices and efficient downstream implementation.

Core Features & Use Cases

  • Phased Project Planning: Generates detailed plans covering requirements gathering, artifact definition, and manifest generation.
  • Agent Domain Framework: Organizes all project artifacts by logical agent domains for consistency and discoverability.
  • Agent Layer Architecture: Integrates with AI agents by defining Genie Spaces as the primary query interface.
  • Plan-as-Contract: Produces machine-readable YAML manifests for downstream orchestrators, ensuring precise implementation.
  • Use Case: When initiating a new Databricks data platform project post-Gold layer (e.g., observability, analytics, agent-based frameworks), use this Skill to create a structured, actionable project plan that guides development from requirements to deployment.

Quick Start

Use the project-planning skill to create a phased project plan for a new Databricks data platform solution, starting with defining key use cases and agent domains.

Frequently Asked Questions about project-planning

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

FAQPage Schema
How do I create a multi-phase project plan for a Databricks data platform solution?▼

You can generate a multi-phase project plan for a Databricks data platform solution by defining key use cases, organizing artifacts by agent domains, and producing machine-readable YAML manifests for downstream orchestrators.

What is the Agent Layer Architecture used for in Databricks project planning?▼

The Agent Layer Architecture in Databricks project planning integrates with AI agents by defining Genie Spaces as the primary query interface, ensuring data platform solutions are structured for AI-driven analysis.

How do I generate manifests for downstream Databricks orchestrators?▼

You generate manifests for downstream Databricks orchestrators by adopting a plan-as-contract approach, which produces machine-readable YAML files detailing the phased project plans for precise implementation.

When do I need to use the Agent Domain Framework for Databricks solutions?▼

You need to use the Agent Domain Framework when planning any Databricks solution post-Gold layer, such as for observability or analytics, to organize all project artifacts by logical domains for consistency.

Can I use this approach to plan Databricks solutions before the Gold layer is complete?▼

No, this project planning approach is specifically designed for use when initiating new Databricks data platform solutions post-Gold layer, such as agent-based frameworks or analytics use cases.

Do I need databricks-expert-agent to define Genie Spaces in my project plan?▼

Yes, defining Genie Spaces as the primary query interface within the Agent Layer Architecture relies on dependencies like databricks-expert-agent to ensure proper integration with your Databricks environment.

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