A comprehensive, practical guide to writing effective Claude prompts — from basic role definition to XML structuring, chain-of-thought, and production system prompts.
Claude responds differently to prompts than other LLMs. Understanding Claude's training approach — Constitutional AI, RLHF, and the emphasis on following explicit instructions — helps you write prompts that consistently get the output you want.
The four pillars of an effective Claude prompt: (1) Role — tell Claude exactly who it is. (2) Task — describe the specific task with clear success criteria. (3) Context — provide all relevant background. (4) Format — specify exactly how you want the output structured.
Use XML tags for complex system prompts. Claude was trained with XML-tagged instructions and responds more consistently to: <instructions>...</instructions>, <context>...</context>, <output_format>...</output_format>.
Chain-of-thought: add "Think through this step by step before responding" or wrap the thinking in <thinking> tags when Claude uses extended thinking mode. This dramatically improves accuracy on reasoning and math tasks.
Few-shot prompting: provide 2-3 examples of your desired input/output pairs. Claude learns from examples faster than long descriptions of what you want.
System prompt template for customer service: "You are a helpful customer service agent for [Company]. You answer questions only using the information in <context>. If the answer is not in the context, say 'I don't have that information' and suggest contacting support@company.com."
Common mistakes: (1) Vague instructions — "write good content" vs "write a 200-word product description focusing on benefit X for audience Y". (2) Missing format spec — always say how long and what structure. (3) No constraints — Claude will guess unless you tell it what NOT to do.
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