What is the main purpose of the Delegation Principle skill?

It ensures the main AI agent acts strictly as a coordinator that delegates all implementation work to specialized subagents rather than performing tasks itself.

Why shouldn't the main agent implement code directly?

Delegation keeps context windows clean, allows for specialized expertise in subagents, and creates a clear, auditable trail of responsibilities.

How does the agent delegate tasks to subagents?

The agent uses the Task tool with a specific subagent_type, passing complete context and waiting for completion before reporting results.

Does this skill work in quick mode?

Yes, even in quick mode, the principle requires the agent to delegate artifact generation and task execution to subagents like the plan-synthesizer and spec-executor.

What are the benefits of using subagents over a single agent?

Subagents offer fresh context windows, specific domain expertise, and a more consistent behavior regardless of the overall task complexity.

AI Task Delegation Principle

Name: AI Task Delegation Principle
Author: DUTSTECH

byDUTSTECH

Productividad y Flujo de Trabajo

Enforces a structured multi-agent architecture where the main AI acts strictly as a coordinator by delegating all implementation tasks to specialized subagents.

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The Delegation Principle skill transforms the Claude Code agent into a high-level orchestrator, ensuring that implementation, research, and coding tasks are never performed by the primary agent itself. By strictly enforcing the use of the Task tool and specialized subagent types, it ensures cleaner context windows, higher auditability, and expert-level results through specialization. This principle prevents the main agent from becoming cluttered with implementation details, maintaining a clear separation of concerns across the entire development workflow.

Características Principales

Enforces strict separation between orchestration and implementation
Maintains clean context windows by offloading implementation logic
Automates task dispatching to specialized subagent types
Standardizes delegation logic even in quick-execution modes
0 GitHub stars
Provides an auditable trail of responsibilities across agent chains

Casos de Uso

Ensuring high-quality code generation through specialized subagent expertise
Managing complex software projects that require distinct planning and execution phases
Maintaining strict governance and audit logs of AI-driven code changes

Acerca de

Características Principales

Enforces strict separation between orchestration and implementation
Maintains clean context windows by offloading implementation logic
Automates task dispatching to specialized subagent types
Standardizes delegation logic even in quick-execution modes
0 GitHub stars
Provides an auditable trail of responsibilities across agent chains

Casos de Uso

Ensuring high-quality code generation through specialized subagent expertise
Managing complex software projects that require distinct planning and execution phases
Maintaining strict governance and audit logs of AI-driven code changes