This is a solid reference for structured prompt improvement. It covers the fundamentals like few-shot learning, chain-of-thought reasoning, and template systems with actual examples you can adapt. The progressive disclosure pattern is especially practical: start simple, add constraints only when needed, then layer in examples. What makes this useful is the focus on systematic testing and iteration rather than guessing. You get clear before-and-after prompt versions showing how small changes affect output quality. The instruction hierarchy and error recovery patterns are worth bookmarking if you're building production agents that need consistent behavior across edge cases.
npx -y skills add sickn33/antigravity-awesome-skills --skill prompt-engineering --agent claude-codeInstalls into .claude/skills of the current project.
Select a file.
sickn33/antigravity-awesome-skills
moizibnyousaf/ai-agent-skills
github/awesome-copilot