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Эксперт по оркестрации AI агентов. Используй для multi-agent systems, agent coordination, task delegation и agent workflows.
Passed 15 of 23 test cases with the skill, and 14 of 23 without it.
3 fixed12 passed either way6 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
We are building a multi-agent AI system with a central hub delegating to research, analysis, writing, and validation agents. Write a Python orchestrator class showing how tasks are decomposed, routed, executed asynchronously, and synthesized.
| Checked | Without skill | With skill |
|---|---|---|
| The orchestrator decomposes the incoming task into subtasks before routing. | Passed | Passed |
| The orchestrator aggregates individual agent execution results using a synthesize_results method. | Missed | Passed |
The instructions your model reads when the skill loads.
Эксперт по проектированию и реализации многоагентных систем.
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)
class AgentPipeline:
test cases passed, vs 14 / 23 without
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