breakdown-plan

Decompose high-level commands into hierarchical Epic, Feature, and Task levels.

Updated Aug 23, 2026
One-click install
npx skills add https://github.com/msageha/maestro_v2 --skill breakdown-plan
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: breakdown-plan
Source: https://github.com/msageha/maestro_v2/tree/main/templates/skills/planner/breakdown-plan
Command: npx skills add https://github.com/msageha/maestro_v2 --skill breakdown-plan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a structured framework to break down complex commands into smaller, manageable tasks, ensuring clarity and efficient execution by AI agents.

Core Features & Use Cases

  • Hierarchical Task Decomposition: Organizes tasks into Epic, Feature, and Task levels.
  • INVEST Criteria Adherence: Ensures tasks are Independent, Negotiable, Valuable, Estimable, Small, and Testable.
  • Bloom's Taxonomy & Persona Mapping: Assigns appropriate cognitive levels and agent personas (researcher, implementer, architect, QA) to tasks.
  • Parallel Execution Guidance: Defines criteria for grouping tasks into waves for parallel processing.
  • Use Case: When given a high-level command like "Refactor the user authentication module," this Skill will break it down into specific, actionable tasks such as "Analyze existing authentication flow," "Design new JWT-based authentication schema," "Implement JWT token generation and validation," and "Write unit tests for new authentication endpoints."

Quick Start

Use the breakdown-plan skill to decompose the command "Implement a new caching layer for the product catalog API".

Frequently Asked Questions about breakdown-plan

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

FAQPage Schema
How do I decompose high-level commands into actionable tasks for AI agents?

Task decomposition breaks high-level commands into a hierarchical structure of Epics, Features, and Tasks. This framework ensures complex commands are broken into smaller, manageable units that AI agents can execute efficiently and clearly.

How does mapping tasks to Bloom's Taxonomy improve agentic execution?

Mapping tasks to Bloom's Taxonomy assigns appropriate cognitive levels to each task. This guides the assignment of specific agent personas like researcher, implementer, architect, or quality-assurance to ensure each task matches the agent's reasoning capability.

What is the best way to ensure decomposed tasks are ready for parallel execution?

Parallel execution is achieved by grouping independent tasks into waves based on specific criteria. The framework uses INVEST criteria to ensure tasks are Independent, Negotiable, Valuable, Estimable, Small, and Testable before grouping them for parallel processing.

When do I need hierarchical task decomposition for my software engineering workflow?

You need hierarchical task decomposition when working with complex commands that require structured breakdown. It organizes large commands into Epic, Feature, and Task levels to provide clarity and ensure efficient execution by AI agents.

Can I use INVEST criteria to validate tasks before assigning them to agent personas?

Yes, INVEST criteria are used to validate that tasks are Independent, Negotiable, Valuable, Estimable, Small, and Testable. This validation occurs before mapping tasks to agent personas like architect or quality-assurance for execution.

What are the limitations of using task decomposition for agentic execution?

The task decomposition framework requires high-level commands to be explicitly defined before breakdown. It focuses on structuring tasks into waves and mapping personas but depends on the underlying AI agents to successfully execute the resulting hierarchical tasks.