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OpenAI wants markdown structure. Anthropic prefers XML tags. Google emphasizes few-shot examples.
So I built a simple agent system that reads the official prompting docs and applies them to the given prompt.
Each optimizer runs a ReAct loop:
- list_provider_docs → discover available guidelines
- read_provider_doc → fetch specific content
- submit_optimization → return structured result
Agent decides what context it needs.
The loop runs until submission:
1. LLM reasons about the task
2. Calls a tool
3. Observes result
4. Repeats
Typically 3-4 iterations. Parallel execution via asyncio.gather; all providers optimize concurrently.
Good to explore the agent design and prompts. Feel free to play with it. Shared the repo here: http://github.com/muratcankoylan/The-Ros……
@LangChainAI @OpenRouterAI