Does the Orchestrator write code directly?

No, the Orchestrator follows a strict 'Iron Law' where it does not write code, read files, or run commands itself. Instead, it delegates these tasks to specialized worker agents to maintain high-level project coordination.

How does the orchestrator keep the user informed?

It uses a consultative approach, asking high-context clarifying questions and providing synthesized progress updates that focus on milestones and outcomes rather than technical internal logs.

What is the benefit of parallel execution in Claude Code?

Parallel execution allows Claude to handle multiple components of a project—such as API design, UI development, and test writing—simultaneously, significantly reducing the total time to completion for complex requests.

What kind of worker agents can be spawned?

The skill can spawn various agent types including Explore agents for research, Plan agents for architecture, and General-Purpose, Junior, or Senior Engineer agents for implementation tasks.

Agent Orchestration

Name: Agent Orchestration
Author: duyet

byduyet

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生产力与工作流

Orchestrates complex multi-step development tasks by coordinating parallel background agents and synthesizing results into cohesive solutions.

关于

This skill transforms Claude into a high-level 'Conductor' designed to handle ambitious, multi-component requests that require more than a single-threaded approach. Instead of performing direct implementation, the orchestrator decomposes complex visions into intelligent task graphs, spawns specialized background workers to handle parallel streams of work, and manages dependencies. It is particularly effective for large-scale codebase investigations, multi-layered feature implementations, or architectural migrations where efficiency and high-level synthesis are paramount. By shielding the user from the underlying machinery, it provides a seamless, professional experience that turns high-level intent into finished reality.

主要功能

Parallel task decomposition and graph management
2 GitHub stars
Consultative decision-making using high-context user questioning
Advanced coordination patterns like Fan-Out, Map-Reduce, and Speculative execution
Intelligent synthesis of disparate agent outputs into unified narratives
Automated background worker delegation and monitoring

使用场景

Conducting comprehensive codebase audits across security, performance, and quality dimensions simultaneously.
Building full-stack features where frontend, backend, and documentation can be developed in parallel.
Executing complex architectural refactors that require speculative testing of multiple implementation hypotheses.

关于

主要功能

Parallel task decomposition and graph management
2 GitHub stars
Consultative decision-making using high-context user questioning
Advanced coordination patterns like Fan-Out, Map-Reduce, and Speculative execution
Intelligent synthesis of disparate agent outputs into unified narratives
Automated background worker delegation and monitoring

使用场景

Conducting comprehensive codebase audits across security, performance, and quality dimensions simultaneously.
Building full-stack features where frontend, backend, and documentation can be developed in parallel.
Executing complex architectural refactors that require speculative testing of multiple implementation hypotheses.