hyperflow-plan

Automate AI engineering pipeline planning by shaping requests, designing specifications, and decomposing tasks.

3|Updated May 14, 2026

Search Tags:#project planning #AI engineering #task decomposition #pipeline management #specification generation

Ready to run

npx skills add https://github.com/Mohammed-Abdelhady/hyperflow --skill hyperflow-plan

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: hyperflow-plan
Source: https://github.com/Mohammed-Abdelhady/hyperflow/tree/main/templates/antigravity/skills/hyperflow-plan
Command: npx skills add https://github.com/Mohammed-Abdelhady/hyperflow --skill hyperflow-plan

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the challenge of shaping requests before code, enabling efficient planning and design for AI engineering pipelines.

Core Features & Use Cases

Request Shaping: Transforms rough prompts and ambiguous ideas into actionable plans.
Design Documentation: Generates specifications and task files for further development.
Task Decomposition: Breaks down complex tasks into manageable sub-tasks for parallel execution.
Use Case: When you have a broad request that needs to be scoped and decomposed into smaller, executable tasks.

Quick Start

Run the hyperflow-plan skill to initiate the planning phase for your AI project.

Frequently Asked Questions about hyperflow-plan

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

FAQPage Schema

How do I decompose complex AI engineering tasks into manageable sub-tasks?▼

AI engineering task decomposition breaks down broad requests into smaller, executable sub-tasks for parallel execution. This approach transforms complex requests into structured components, enabling efficient project execution and clear development pathways through automated specification generation.

What is the best way to generate specifications from rough prompts for AI pipelines?▼

Generating specifications from rough prompts involves request shaping to transform ambiguous ideas into actionable plans. This process produces detailed design documentation and task files, providing a structured blueprint for subsequent AI pipeline development phases.

Can I use automated planning to scope ambiguous AI project requests before coding?▼

Automated planning can scope ambiguous AI project requests before coding by shaping the initial input into actionable plans. It generates specifications and decomposes tasks, ensuring requirements are clearly defined and structured prior to actual development.

Do I need any specific dependencies to automate AI project management and task decomposition?▼

Automating AI project management and task decomposition requires no specific external dependencies. The planning process operates independently to shape requests, design specifications, and break down tasks without needing additional external frameworks or libraries.

When should I use task decomposition in AI engineering pipeline management?▼

Task decomposition should be used in AI engineering pipeline management when you have a broad request that needs strict scoping. It is essential for breaking down complex tasks into parallel sub-tasks, ensuring efficient execution and clear planning.