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anthropic-prompt-engineer

Master Anthropic's prompt engineering techniques to generate new prompts or improve existing ones using best practices for Claude AI models.

معلومات المصدر

المستودع
JantonioFC/skillsbank
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٤ أغسطس ٢٠٢٦ في ٠٣:٠٧
لغة SKILL.md المكتشفة
الإنجليزية
النجوم
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التفرعات
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خيارات التثبيت

يُحدَّد Prompt الذي يراجع المصدر أولًا بشكل افتراضي. يمكنك التبديل إلى أمر مباشر أو تنزيل نسخة محلية.

مراجعة ملفات المصدر

اقرأ SKILL.md وأي ملفات مرافقة يعرضها SkillsMP قبل أن تقرر التثبيت.

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SKILL.md
تعليمات المصدر · معاينة للقراءة فقط
name
anthropic-prompt-engineer
description
Master Anthropic's prompt engineering techniques to generate new prompts or improve existing ones using best practices for Claude AI models.
risk
safe
source
community
license
MIT
# Anthropic Prompt Engineer Master the art and science of prompt engineering with Anthropic's proven techniques. Generate new prompts from scratch or improve existing ones using best practices for Claude AI models (Claude 4.x, Sonnet, Opus, Haiku). ## What This Skill Does Helps you create and optimize prompts for Claude AI using Anthropic's official techniques: - **Generate new prompts** - Build effective prompts from requirements - **Improve existing prompts** - Optimize prompts for better results - **Apply best practices** - Use proven techniques from Anthropic - **Avoid common mistakes** - Prevent hallucinations and unclear outputs - **Optimize for Claude 4.x** - Leverage latest model capabilities - **Structure complex prompts** - Build multi-step, production-ready prompts ## Why Prompt Engineering Matters **Without proper prompting:** - Inconsistent or incorrect outputs - Hallucinations and made-up information - Unclear or verbose responses - Wasted tokens and API calls - Poor performance on complex tasks - Difficulty reproducing results **With engineered prompts:** - Precise, reliable outputs - Factual, grounded responses - Clear, formatted results - Efficient token usage - Excellent complex task performance - Reproducible, production-ready results ## Quick Start ### Generate a New Prompt ``` Using the anthropic-prompt-engineer skill, create a prompt that: - Extracts structured data from customer emails - Returns JSON format - Handles missing information gracefully - Includes 2 examples ``` ### Improve an Existing Prompt ``` Using the anthropic-prompt-engineer skill, improve this prompt: "Analyze this code and tell me if there are bugs" Make it more effective using Anthropic's best practices. ``` ## Core Techniques Summary ### 1. Be Clear and Direct Provide explicit, unambiguous instructions. Claude 4.x excels with precise direction. ### 2. Use XML Tags for Structure Organize prompts with semantic tags like `<instructions>`, `<example>`, `<context>`. ### 3. Chain of Thought (CoT) Ask Claude to think step-by-step for complex reasoning. ### 4. Prefilling Start Claude's response to guide format and style. ### 5. Few-Shot Examples Provide 2-5 diverse examples showing the pattern you want. ### 6. Role Assignment Give Claude a specific role or persona for appropriate context. ## Reference Materials All techniques, examples, and templates are available in the `references/` directory: - **core_techniques.md** - Essential techniques with examples - **advanced_techniques.md** - Advanced methods and optimization - **common_mistakes.md** - Pitfalls to avoid - **claude_4_best_practices.md** - Claude 4.x specific guidance - **prompt_templates.md** - Ready-to-use templates ## Usage Examples ### Example 1: Generate a Data Extraction Prompt Create a prompt that extracts names, emails, and phone numbers from business cards. ### Example 2: Improve a Vague Prompt Transform "Write about machine learning" into a structured, effective prompt. ### Example 3: Debug a Failing Prompt Fix inconsistent outputs by adding structure, examples, and format specification. ## Best Practices Checklist - [ ] Instructions are clear and specific - [ ] Output format is explicitly defined - [ ] Examples align with desired behavior - [ ] XML tags separate different sections - [ ] Context is minimal but sufficient - [ ] Edge cases are addressed - [ ] Tested on diverse inputs - [ ] Token usage is optimized ## Key Principles 1. **Empirical Approach** - Test, measure, iterate 2. **Context as Resource** - Every token counts 3. **Clarity Over Cleverness** - Explicit instructions work best 4. **Examples Teach Best** - Show, don't just tell 5. **Structure Helps** - Organization reduces confusion 6. **Iteration Improves** - Refine based on results ## Summary Master prompt engineering to create: - Reliable and consistent outputs - Production-ready prompts - Token-efficient solutions - Easy to maintain systems Apply Anthropic's proven techniques for best results. --- **Remember:** Good prompts are engineered, not guessed. ## When to Use Master Anthropic's prompt engineering techniques to generate new prompts or improve existing ones using best practices for Claude AI models. Covers: What This Skill Does, Why Prompt Engineering Matters, Generate a New Prompt, Improve an Existing Prompt, Core Techniques Summary.
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