AI agents work best when they have the right information at the right time. This skill shows you how to set up that information clearly and simply. You can improve agent output quality by giving it a rules file, relevant code, and error logs.
Use the context hierarchy to organize what the agent sees. Start with persistent rules that apply to the whole project. Then add specs for the current feature. Then load relevant source files. Finally feed error output as needed. This keeps the agent focused and reduces mistakes.
Global
mkdir -p ~/.claude/skills/context-engineeringProject
mkdir -p .claude/skills/context-engineeringSource 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
Prompt Engineering Patternswshobson/agents
Master advanced prompt engineering patterns to get reliable and powerful AI outputs every time
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