prompt-engineering
byancoleman· 58 skills
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).
How to install prompt-engineering?
ancoleman/ai-design-components/prompt-engineering
$npx -y skills add ancoleman/ai-design-components --skill prompt-engineeringInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/ancoleman/ai-design-components" --skill "ancoleman/ai-design-components/prompt-engineering"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/ancoleman/ai-design-components" that are relevant to the current task. Run `npx skills add "https://github.com/ancoleman/ai-design-components"` and select the relevant skills, then follow their instructions.
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