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llm-aidata-ai

prompt-engineering

Engineer effective LLM prompts using zero-shot, few-shot, chain-of-thought, and structured output techniques. Use when building LLM applications requiring reliable outputs, implementing RAG systems, creating AI agents, or optimizing prompt quality and cost. Covers OpenAI, Anthropic, and open-source models with multi-language examples (Python/TypeScript).

vuralserhat86
maintainer
vuralserhat86
์—…๋ฐ์ดํŠธ๋จ 1/3/2026
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quick start

Installation and usage

Engineer effective LLM prompts using zero-shot, few-shot, chain-of-thought, and structured output techniques. Use when building LLM applications requiring reliable outputs, implementing RAG systems, creating AI agents, or optimizing prompt quality and cost. Covers OpenAI, Anthropic, and open-source models with multi-language examples (Python/TypeScript).

์„ค์น˜
$ install --globalskills.sh
์‚ฌ์šฉ๋ฒ•

์„ค์น˜ ํ›„ ํ„ฐ๋ฏธ๋„์—์„œ ๋‹ค์Œ ๋ช…๋ น์„ ์‹คํ–‰ํ•˜์—ฌ ์ด ์Šคํ‚ฌ์„ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค:

skills use prompt-engineering