What is Task Layering?

Task Layering is a project management method that breaks down software specifications into stratified tiers based on complexity and dependencies to enable efficient parallel execution.

What output files are generated?

It generates a master 'layered-tasks.md' file and individual task files for each assigned agent (e.g., 'claude-tasks.md', 'copilot-tasks.md') for easy distribution.

How does the complexity stratification work?

Tasks are rated from 0 to 3: Trivial ( 2h), ensuring that the most difficult tasks are handled by high-reasoning models.

Which AI agents does this skill support?

The skill assigns tasks to specialized models including Claude (Architecture), Copilot (UI/Data), Qwen (Performance), Gemini (Docs), and Codex (Testing).

Task Layering & Agent Orchestrator

Name: Task Layering & Agent Orchestrator
Author: vanman2024

byvanman2024

Productividad y Flujo de Trabajo

Stratifies project specifications into complexity-based layers and assigns tasks to specialized AI agents for optimized parallel execution.

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Task Layering is a workflow optimization skill designed to transform project requirements into a structured, multi-tiered execution plan. It categorizes tasks by complexity on a four-point scale and organizes them into three strategic phases: Foundation, Parallel, and Integration. By automatically delegating responsibilities to the most suitable AI models—such as Claude for architectural design and Codex for testing—it eliminates development bottlenecks and maximizes team productivity through intelligent task distribution and dependency mapping.

Características Principales

Three-tier workflow organization (Foundation, Parallel, Integration)
0 GitHub stars
Automated multi-agent assignment based on model strengths
Dependency identification for sequential and concurrent planning
Four-level complexity stratification (Trivial to Complex)
Automatic generation of agent-specific task distribution files

Casos de Uso

Converting raw project specifications into an actionable, prioritized roadmap
Optimizing development cycles by identifying parallelizable work streams
Orchestrating large-scale feature development across multiple AI assistants

Acerca de

Características Principales

Three-tier workflow organization (Foundation, Parallel, Integration)
0 GitHub stars
Automated multi-agent assignment based on model strengths
Dependency identification for sequential and concurrent planning
Four-level complexity stratification (Trivial to Complex)
Automatic generation of agent-specific task distribution files

Casos de Uso

Converting raw project specifications into an actionable, prioritized roadmap
Optimizing development cycles by identifying parallelizable work streams
Orchestrating large-scale feature development across multiple AI assistants