When should I avoid using the orchestration patterns?

Orchestration is overkill for simple one-shot tasks, single-file edits, or basic questions that can be answered within a single context window.

What is the primary purpose of the Orchestrator Conductor skill?

It allows Claude to act as a central conductor that breaks down complex user requests into discrete tasks, delegating them to background worker agents rather than trying to perform all the work in a single context.

How does this skill improve performance for large projects?

By using a parallel-first workflow, the skill spawns multiple agents at once to handle different parts of a codebase simultaneously, significantly reducing the time required for deep analysis or multi-file edits.

Which Claude models does the orchestrator use?

It uses Model-Matched Specialization: Haiku for mechanical data gathering, Sonnet for implementation and testing, and Opus for high-level architectural judgment and synthesis.

How do I monitor the progress of the agents?

You can use the '/orchestrate status' command to see a visual breakdown of tasks categorized as pending, in-progress, completed, or blocked by dependencies.

Orchestrator Conductor

Name: Orchestrator Conductor
Author: bigadamknight

bybigadamknight

生産性とワークフロー

Orchestrates complex multi-agent workflows by decomposing large tasks into parallelized sub-tasks managed by specialized AI workers.

概要

The Orchestrator Conductor skill transforms Claude into a high-level project manager capable of handling massive technical debt and complex migrations. Instead of attempting to process everything in a single window, it utilizes five core orchestration patterns—including Task Graph Management and Parallel-First Workflows—to delegate work across a swarm of specialized agents. By matching task complexity to the most efficient model (Haiku, Sonnet, or Opus), it preserves orchestration capacity and context while dramatically increasing the speed and scale of code analysis and implementation.

主な機能

Model-matched specialization for cost and performance optimization
Automated task decomposition with explicit dependency tracking
Parallel-first execution to run multiple worker agents simultaneously
0 GitHub stars
Real-time orchestration lifecycle management (pause, resume, abort)
Worker constraints that prevent sub-agent sprawl and focus execution

ユースケース

Comprehensive codebase security audits and vulnerability scanning
Large-scale architectural refactoring across multiple service layers
Automated documentation generation and mapping for legacy repositories

概要

主な機能

Model-matched specialization for cost and performance optimization
Automated task decomposition with explicit dependency tracking
Parallel-first execution to run multiple worker agents simultaneously
0 GitHub stars
Real-time orchestration lifecycle management (pause, resume, abort)
Worker constraints that prevent sub-agent sprawl and focus execution

ユースケース

Comprehensive codebase security audits and vulnerability scanning
Large-scale architectural refactoring across multiple service layers
Automated documentation generation and mapping for legacy repositories