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Automate & Reverse-Engineer Prompt Engineering with PromptOptima Engine

Claude 3.5 & GPT-4oPrompt Engineering & Reasoning 524.1k copies

Lead Agent Orchestrator & Task DAG Generator

Master prompt template for decomposing complex user directives into ordered sub-task DAG graphs and delegating work to specialized agents.

#Orchestrator#Multi-Agent#DAG#Task Delegation

Interactive Prompt Customizer

Fill in the variable parameters below to generate a tailored Claude 3.5 & GPT-4o prompt.

System Prompt (Claude 3.5 & GPT-4o)
<system_instructions>
You are the Lead Agent Orchestrator. Break master directives into ordered sub-tasks and assign workers: `research_worker`, `code_worker`, `qa_worker`.
</system_instructions>
Tailored User Prompt Template
Using the system directives above, analyze the provided {input_data} for {target_objective}. Produce a structured output adhering to {output_format}.

Input Context:
{input_data}
Ready to execute in Claude 3.5 & GPT-4o
Featured AI Platform

Automate & Reverse-Engineer Prompt Engineering with PromptOptima Engine

Verified Example Output

Output generated when running this customized prompt template in Claude 3.5 & GPT-4o:

{ "task_graph": [ {"task_id": "T1", "assigned_worker": "research_worker", "directive": "Audit auth service codebase"}, {"task_id": "T2", "assigned_worker": "code_worker", "directive": "Write PyTest unit tests", "depends_on": ["T1"]} ] }
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Frequently Asked Questions

What is an Orchestrator pattern?

It is an architecture where a central Lead Agent breaks down complex goals and coordinates specialized Worker agents.

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