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orchestrator-design协调器设计

Agent Skill

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

总安装

349

周安装

14

GitHub Stars

61

下载量

113
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:orchestrator-design(协调器设计)
来源仓库:https://github.com/melodic-software/claude-code-plugins
仓库路径:skills/orchestrator-design
安装命令:
npx skills add https://github.com/melodic-software/claude-code-plugins --skill orchestrator-design
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/melodic-software/claude-code-plugins --skill orchestrator-design

简介

用于辅助界面设计、视觉规范和布局优化。

  • 适合整理页面结构、生成 UI 方案或改进组件层级。
  • 需结合现有品牌和设计系统使用,不应仅堆砌装饰元素。
  • 涉及真实页面改动时应通过截图或浏览器预览检查文本溢出和对齐。
  • orchestrator-design 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Orchestrator Design Skill

Design O-Agent (Orchestrator Agent) systems for managing fleets of specialized agents.

Purpose

Guide the architectural design of orchestrator systems that create, command, monitor, and delete specialized agents through a single unified interface.

When to Use

  • Designing multi-agent systems
  • Building fleet management architecture
  • Creating scalable agent workflows
  • Implementing the Single Interface Pattern

Prerequisites

  • Understanding of the Three Pillars (@three-pillars-orchestration.md)
  • Familiarity with agent lifecycle patterns (@agent-lifecycle-crud.md)
  • Access to Claude Agent SDK documentation

SDK Requirement

Implementation Note: Orchestrator patterns require Claude Agent SDK with custom MCP tools. Claude Code subagents cannot spawn other subagents.

Design Process

Step 1: Define Orchestration Scope

Answer these questions:

  • What workflows will be orchestrated?
  • What agent types are needed?
  • What is the expected scale?
  • What observability is required?

Output: Scope document (requirements and constraints)

Step 2: Design Agent Templates

For each agent type needed:

TemplatePurposeModelTools
scout-fastQuick reconnaissanceHaikuRead, Glob, Grep
builderCode implementationSonnetRead, Write, Edit, Bash
reviewerCode reviewSonnetRead, Grep, Glob, Bash
plannerTask planningSonnetRead, Glob, Grep

Template Structure:

---
name: template-name
description: What this agent does
tools: [tool1, tool2]
model: sonnet|haiku
---

# System Prompt

[Agent-specific instructions]

Step 3: Design Orchestrator System Prompt

The orchestrator needs a specific identity:

# Orchestrator Agent

## Purpose
Manage and coordinate specialized agents to accomplish complex tasks.
You do NOT perform work directly - you orchestrate other agents.

## Capabilities
- Create specialized agents from templates
- Command agents with detailed prompts
- Monitor agent progress
- Aggregate and report results
- Delete agents when work is complete

## Workflow Pattern
1. Analyze task requirements
2. Create appropriate agents
3. Command agents with detailed instructions
4. Monitor progress
5. Aggregate results
6. Report to user
7. Delete agents

## Context Protection
- Keep your context focused on orchestration
- Delegate detailed work to specialized agents
- Do not read files directly
- Do not write code

Step 4: Define Management Tools

Design the MCP tools for agent management:

ToolPurposeParameters
create_agentSpin up new agenttemplate, name
command_agentSend prompt to agentagent_id, prompt
check_agent_statusGet agent progressagent_id
list_agentsView all active agents-
delete_agentClean up agentagent_id
read_agent_logsView agent responsesagent_id

Step 5: Design Observability Layer

Essential metrics to track:

MetricPurpose
Agent statusKnow what's running
Context usageMonitor token consumption
CostsTrack spend per agent
Tool callsSee what agents are doing
ResultsVerify outputs
TimeMeasure execution duration

Observability Components:

  1. Agent Cards - Status, model, context, cost per agent
  2. Event Stream - Real-time log of all activities
  3. Cost Tracking - Per-agent and total costs
  4. Result Inspector - consumed/produced assets
  5. Log Viewer - Filterable activity history

Step 6: Design Workflow Phases

Standard orchestration workflow:

Phase 1: Scout
├── Create scouts (parallel)
├── Command each with specific area
├── Monitor until complete
└── Aggregate findings

Phase 2: Build
├── Create builder
├── Command with scout reports
├── Monitor implementation
└── Aggregate changes

Phase 3: Review
├── Create reviewer
├── Command to verify implementation
├── Monitor review
└── Generate final report

Cleanup: Delete all agents

Step 7: Plan Deployment Architecture

Required components for SDK implementation:

ComponentPurpose
Claude Agent SDKCore orchestration
MCP ServersAgent management tools
DatabaseAgent state persistence
WebSocketReal-time updates
UI/CLIUser interface

Output Format

When designing an orchestrator system, provide:

## Orchestrator System Design

**Name:** [system-name]
**Purpose:** [1-2 sentences]
**Scale:** [expected agent count and concurrency]

### Agent Templates

| Template | Purpose | Model | Tools |
| --- | --- | --- | --- |
| ... | ... | ... | ... |

### Orchestrator Configuration

**System Prompt:** [included or file reference]
**Management Tools:** [list of MCP tools]
**Observability:** [metrics and components]

### Workflow Design

[Phase diagram with agent creation/deletion points]

### Architecture

[Deployment diagram with components]

### Implementation Notes

[SDK considerations, constraints, scaling factors]

Design Checklist

  • Orchestration scope defined
  • Agent templates designed
  • Orchestrator system prompt written
  • Management tools specified
  • Observability layer planned
  • Workflow phases designed
  • Deployment architecture planned

Anti-Patterns

AvoidWhyInstead
Orchestrator doing workContext pollutionDelegate everything
Missing observabilityFlying blindTrack all metrics
Keeping dead agentsResource wasteDelete when done
No lifecycle managementCan't scaleCRUD operations
Generic agentsUnfocused workSpecialized templates

Cross-References

  • @three-pillars-orchestration.md - Framework foundation
  • @single-interface-pattern.md - O-Agent architecture
  • @agent-lifecycle-crud.md - Lifecycle management
  • @multi-agent-context-protection.md - Context boundaries
  • @results-oriented-engineering.md - Result patterns

Version History

  • v1.0.0 (2025-12-26): Initial release

Last Updated

Date: 2025-12-26 Model: claude-opus-4-5-20251101

适合场景

01

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02

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能力概览

能力 1

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能力 2

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能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Antigravity

24.78%
按下载量换算28

trae

23.53%
按下载量换算27

windsurf

17.32%
按下载量换算20

Claude Code

12.84%
按下载量换算15

Codex

7.4%
按下载量换算8

Gemini CLI

3.2%
按下载量换算4

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/melodic-software/claude-code-plugins --skill orchestrator-design;npx skills add melodic-software/claude-code-plugins --skill "orchestrator-design" 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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