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team-orchestrator

Orchestrate agent teams to allocate tasks and aggregate build/test results.

Updated Aug 23, 2026
Search Tags:#automation#dependency management#orchestration#agent teams#task distribution#file ownership#result aggregation
One-click install
npx skills add https://github.com/JYHTHEGREAT/jyh-system --skill team-orchestrator-jyhthegreat
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: team-orchestrator
Source: https://github.com/JYHTHEGREAT/jyh-system/tree/main/archive/reusable/large-scale/skills/team-orchestrator
Command: npx skills add https://github.com/JYHTHEGREAT/jyh-system --skill team-orchestrator-jyhthegreat

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The team-orchestrator skill removes the friction of coordinating multiple autonomous agents by assembling teams, assigning file ownership, managing task dependencies, and aggregating results to prevent conflicts and ensure end-to-end verification.

Core Features & Use Cases

  • Team composition templates: Select role templates (frontend, backend, QA, investigator, implementer) and scale team size based on task scope.
  • Deterministic task distribution: Split work into owner-assigned tasks with dependency (addBlockedBy) relationships and file ownership rules to avoid overwrite races.
  • Execution & recovery: Spawn subagents, require plan approval when needed, support self-claiming of unblocked tasks, detect deadlocks/collisions, and aggregate build/type/test results into a final report.
  • Use Case: Run an orchestration to implement a cross-cutting feature where multiple files and services must be changed, then produce an integrated verification summary for handoff.

Quick Start

Orchestrate a team to implement and verify the authentication module by assigning file owners, defining task dependencies, and running the orchestration until build and tests pass.

Frequently Asked Questions about team-orchestrator

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

FAQPage Schema
How do I coordinate multiple autonomous agents to prevent file overwrite races during feature implementation?▼

Multi-agent orchestration coordinates autonomous agents by assigning deterministic file ownership rules and task dependencies, preventing overwrite races during feature implementation. It splits work into owner-assigned tasks with blocked-by relationships to ensure conflict-free execution.

What is multi-agent task dependency management and how do blocked-by relationships work?▼

Task dependency management organizes sub-tasks using blocked-by relationships, ensuring an agent only self-claims an unblocked task after its prerequisites finish. This mechanism prevents execution deadlocks and enforces logical sequencing across distributed agent teams.

How do I set up agent teams for software engineering workflows like refactoring and bug investigation?▼

Setting up agent teams involves selecting role templates like frontend, backend, QA, or investigator, then scaling team size based on task scope. You define file owners and task dependencies before spawning subagents to execute refactoring or bug investigation workflows.

Do I need an environment flag to enable experimental agent teams for task distribution?▼

Yes, multi-agent task distribution requires enabling the CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS environment flag. This prerequisite activates the orchestration capabilities needed to spawn subagents, enforce plan approval gating, and manage deterministic file ownership separation.

How does result aggregation work when running build and test verification across multiple agents?▼

Result aggregation collects build, type, and test outputs from all spawned subagents into a final integrated report. The orchestration detects deadlocks and collisions during execution, then compiles verification results to confirm end-to-end delivery before handoff.

What are the limitations of using plan approval gating in multi-agent orchestration?▼

Plan approval gating in multi-agent orchestration requires manual intervention before subagents execute complex tasks, which can bottleneck automated pipelines. However, it prevents uncontrolled autonomous execution when task dependencies and file ownership rules need human verification before proceeding.

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