Prompt engineering helps you get the best results from AI models. You can teach them to think step by step with chain-of-thought reasoning. You can also give examples with few-shot learning for more accurate answers.
Structured outputs like JSON make it easy to use AI responses in your code. This skill shows you how to design prompt templates that work every time. You will learn to debug and improve prompts that give inconsistent results.
These techniques are used in production apps and specialized AI assistants. Master them to control model behavior and output format. Your prompts will be more reliable and powerful.
Global
mkdir -p ~/.claude/skills/prompt-engineering-patternsProject
mkdir -p .claude/skills/prompt-engineering-patternsSource Repository
Cavemanjuliusbrussee/caveman
Talk like a smart caveman to save tokens without losing technical accuracy
Cavemanmattpocock/skills
Caveman mode for AI cuts token count 75% without losing technical accuracy
Enhance Promptgoogle-labs-code/stitch-skills
Turn vague UI ideas into clear, polished prompts with design system consistency
Humanizer Zhop7418/humanizer-zh
Remove AI writing patterns to make your text sound natural and human
Gws Modelarmorgoogleworkspace/cli
Filter harmful user content automatically with Google Model Armor for safety
Context Engineeringaddyosmani/agent-skills
Optimize your agent's context to improve output quality and focus
Writetw93/waza
Rewrite your prose to sound human and natural every time
Ai Prompt Engineering Safety Reviewgithub/awesome-copilot
Analyze and improve AI prompts for safety, bias, and effectiveness