Free Claude Prompt Generator & XML Structurer
Engineer crystal-clear coding, analysis, and writing prompts tailored to Anthropic Claude with explicit context and negative constraints.
AI Prompt Engineering Studio
100% Client-Side Prompt Optimization
<!-- Optimized for: Claude (Anthropic) | Category: Coding & Architecture -->
# ROLE & PERSONA
You are acting as an expert Principal Software Architect, Staff Frontend Engineer, and Lead Systems Designer specializing in ultra-reliable, clean, scalable code. Your tone must remain strictly professional, authoritative, and free of unnecessary fluff.
# CONTEXT & PRIMARY OBJECTIVE
Refactor a monolithic Node.js backend module into a clean hexagonal domain architecture with TypeScript
Target Depth: Thorough, production-grade depth with zero omitted steps or hand-waving.
# SPECIFIC INSTRUCTIONS & METHODOLOGY
1. Analyze the core objective with high domain accuracy.
2. Provide practical, high-value execution steps adhering to best industry standards.
3. Include concrete examples, real-world context, and rationale for critical decisions.
4. Ensure every recommendation is pragmatic and directly usable.
# CONSTRAINTS & NEGATIVE PROMPTING
- Do NOT use generic conversational filler (e.g., "Sure, I'd be happy to help", "In conclusion").
- Do NOT provide superficial high-level bullet points without concrete implementation details.
- Avoid cliché buzzwords and robotic corporate jargon.
- Verify all assumptions and highlight any trade-offs or edge-case risks.
# REQUIRED OUTPUT FORMAT
Present the complete solution as a Step-by-Step Guide. Use clean markdown headers, code fences, or tables where appropriate.This specialized prompt builder creates XML-formatted system instructions designed specifically for Anthropic Claude models, clearly separating background context, tasks, and constraints so Claude delivers accurate answers without conversational filler.
How to Structure Prompts for Claude
Input Your Objective or Code Task
Describe your software task, complex essay, or analytical inquiry.
Apply Claude XML Tag Hierarchy
Organize context, inputs, and constraints into clean XML tags like `<context>` and `<instructions>`.
Copy and Execute in Claude
Paste into Claude.ai or the Anthropic Console for nuanced, deterministic responses.
Why Structure Prompts for Claude
Anthropic Best Practices Aligned
Incorporates XML tags and chain-of-thought scratchpads recommended in Anthropic's prompt engineering documentation.
Superior Coding Precision
Forces Claude 3.5 to consider edge cases, types, and architecture before generating code.
100% Local & Private
Ensure your proprietary codebase snippets and startup ideas are never uploaded to third-party logs.
Best Use Cases
Full-Stack Code Refactoring & Audits
Long-Form Technical Documentation
Deep Strategic & Financial Analysis
Combine this utility with our complementary tool to validate and format JSON payloads returned by Claude API calls.
Anthropic Claude XML Tag Structuring Architecture
Anthropic's Claude models are specifically trained on XML-delimited prompts. Enclosing instructions, contextual data, and constraints inside semantic XML tags (<instructions>, <context>, <constraints>) prevents prompt injection and enhances instruction adherence.
| XML Tag Container | Recommended Placement | Primary Function | Adherence Advantage |
|---|---|---|---|
| <context> | Top of the prompt | Defines project background, system architecture, audience, and operational context | Separates general background from active execution commands |
| <instructions> | Middle of the prompt | Numbered step-by-step tasks, business logic rules, and analysis workflows | Enforces sequential execution without omitting intermediate steps |
| <constraints> | Immediately after instructions | Negative constraints, tone guardrails, and forbidden conversational boilerplate | Prevents preamble phrases like 'Certainly, here is the answer' and enforces brevity |
| <examples> | Before the input data | Few-shot gold-standard demonstration pairs showing ideal input and expected output | Drastically reduces formatting deviations in automated API workflows |
| <formatting> | End of the prompt | Explicit schema definition (Markdown tables, JSON, code blocks, bullet points) | Guarantees output is immediately parseable by downstream software or workflows |
Industry Pro Tips & Execution Guidelines
- Include the constraint 'Do not include conversational preamble. Begin your response immediately with the requested content' to save tokens.
- Instruct Claude to 'Think step-by-step inside <thinking> tags before providing the final answer' to activate chain-of-thought reasoning.
- When asking Claude to analyze an uploaded document or code snippet, enclose the raw text in <source_document> tags to isolate it from instructions.
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