If you're building production LLM apps and tired of inconsistent outputs, this handles the advanced prompt engineering patterns that actually matter. It covers structured outputs with Pydantic schemas, chain-of-thought reasoning with self-verification, and dynamic few-shot example selection using semantic similarity. The JSON mode examples alone will save you hours of parsing headaches. What I like most is the progressive disclosure approach, starting simple and adding complexity only when needed. It includes concrete patterns for A/B testing prompts, handling malformed responses, and building reusable template systems with proper variable interpolation.
npx -y skills add wshobson/agents --skill prompt-engineering-patterns --agent claude-codeInstalls into .claude/skills of the current project.
Select a file.
sickn33/antigravity-awesome-skills
moizibnyousaf/ai-agent-skills
github/awesome-copilot