ai-agent-orchestrator
Эксперт по оркестрации AI агентов. Используй для multi-agent systems, agent coordination, task delegation и agent workflows.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/dengineproblem/agents-monorepo --skill ai-agent-orchestrator- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads ai-agent-orchestrator automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
AI Agent Orchestrator Expert
Эксперт по проектированию и реализации многоагентных систем.
Основные принципы
Иерархия агентов
- Оркестратор: Главный координатор, делегирует задачи
- Специализированные агенты: Для конкретных доменов (исследования, анализ, код)
- Утилитарные агенты: Вспомогательные функции (валидация, форматирование)
- Мониторинг: Здоровье системы и обработка ошибок
Паттерны архитектуры
Hub and Spoke
class OrchestratorAgent:
def __init__(self):
self.agents = {
'researcher': ResearchAgent(),
'analyzer': AnalysisAgent(),
'writer': WritingAgent(),
'validator': ValidationAgent()
}
async def orchestrate_task(self, task):
subtasks = self.decompose_task(task)
results = []
for subtask in subtasks:
agent_type = self.route_task(subtask)
result = await self.agents[agent_type].execute(subtask)
results.append(result)
return self.synthesize_results(results)
Pipeline Pattern
class AgentPipeline:
def __init__(self):
self.stages = [
DataIngestionAgent(),
ProcessingAgent(),
AnalysisAgent(),
OutputAgent()
]
async def execute_pipeline(self, input_data):
data = input_data
for stage in self.stages:
try:
data = await stage.process(data)
except Exception as e:
return await self.handle_pipeline_error(stage, e, data)
return data
Маршрутизация задач
class TaskRouter:
def __init__(self):
self.agent_capabilities = {
'code_analysis': ['python', 'javascript', 'sql'],
'research': ['web_search', 'document_analysis'],
'writing': ['technical', 'creative', 'business']
}
self.agent_load = {}
def route_task(self, task):
required_skills = self.extract_skills(task)
capable_agents = [
agent_id for agent_id, skills in self.agent_capabilities.items()
if self.has_required_skills(skills, required_skills)
]
return self.select_least_loaded_agent(capable_agents)
Межагентная коммуникация
@dataclass
class AgentMessage:
sender_id: str
receiver_id: str
message_type: MessageType
payload: Dict[str, Any]
correlation_id: str
timestamp: float
priority: int = 5
class MessageBus:
async def send_message(self, message: AgentMessage):
await self.validate_message(message)
await self.route_message(message)
await self.log_message(message)
Обработка ошибок
Circuit Breaker
class AgentCircuitBreaker:
def __init__(self, failure_threshold=5, timeout=60):
self.failure_count = 0
self.failure_threshold = failure_threshold
self.state = 'CLOSED'
async def call_agent(self, agent, task):
if self.state == 'OPEN':
if time.time() - self.last_failure_time > self.timeout:
self.state = 'HALF_OPEN'
else:
raise CircuitBreakerOpenError()
try:
result = await agent.execute(task)
if self.state == 'HALF_OPEN':
self.reset()
return result
except Exception as e:
self.record_failure()
raise
Graceful Degradation
class ResilientOrchestrator:
def __init__(self):
self.agent_priorities = {
'primary': ['gpt-4', 'claude-3'],
'fallback': ['gpt-3.5', 'local-model'],
'emergency': ['rule-based-agent']
}
async def execute_with_fallback(self, task):
for tier in ['primary', 'fallback', 'emergency']:
for agent_id in self.agent_priorities[tier]:
try:
if await self.is_agent_healthy(agent_id):
return await self.execute_on_agent(agent_id, task)
except Exception:
continue
raise AllAgentsFailedError()
Лучшие практики
- Реализуйте комплексное логирование с correlation ID
- Отслеживайте метрики производительности агентов
- Используйте распределенную трассировку для сложных workflows
- Валидируйте всю межагентную коммуникацию
- Проектируйте агентов как stateless когда возможно
- Используйте очереди сообщений для развязки
FAQ
What does the ai-agent-orchestrator skill do?
Эксперт по оркестрации AI агентов. Используй для multi-agent systems, agent coordination, task delegation и agent workflows.
How do I install ai-agent-orchestrator?
Run npx skills add https://github.com/dengineproblem/agents-monorepo --skill ai-agent-orchestrator in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/ai-agent-orchestrator/ (personal) or .claude/skills/ai-agent-orchestrator/ (project).
Which AI agents can use ai-agent-orchestrator?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is ai-agent-orchestrator safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains ai-agent-orchestrator?
It is published by dengineproblem in dengineproblem/agents-monorepo. It has 69 recorded installs.
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