prompt-engineering-suite

npx skills add majiayu000/claude-skill-registry --skill prompt-engineering-suite --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

# Prompt Engineering Suite Design, version, and optimize prompts for production LLM applications. ## Overview - Designing prompts for new LLM features - Improving accuracy with Chain-of-Thought reasoning - Few-shot learning with example selection - Managing prompts in production (versioning, A/B testing) - Automatic prompt optimization with DSPy ## Quick Reference ### Chain-of-Thought Pattern ```python from langchain_core.prompts import ChatPromptTemplate COT_SYSTEM = """You are a helpful assistant that solves problems step-by-step. When solving problems: 1. Break down the problem into clear steps 2. Show your reasoning for each step 3. Verify your answer before responding 4. If uncertain, acknowledge limitations Format your response as: STEP 1: [description] Reasoning: [your thought process] STEP 2: [description] Reasoning: [your thought process] ... FINAL ANSWER: [your conclusion]""" cot_prompt = ChatPromptTemplate.from_messages([ ("system", COT_SYSTEM), ("human", "Problem: {problem}\n\nThink through this step-by-step."), ]) ``` ### Few-Shot with Dynamic Examples ```python from langchain_core.prompts import FewShotChatMessagePromptTemplate examples = [ {"input": "What is 2+2?", "