Transform rough ideas into production-ready LLM prompts. Supports Claude, GPT, Llama, and other models. Uses advanced techniques like Chain-of-Thought, Constitutional AI, and RAG optimization. Ideal for operations teams automating workflows.
git clone https://github.com/repo-phuocdt/prompt-engineer-skill.gitThe prompt-engineer-skill is a Claude Code automation skill designed to help users transform rough ideas into production-ready prompts for large language models (LLMs). This intermediate-level skill allows developers and AI practitioners to streamline the process of crafting effective prompts, ensuring that they can maximize the potential of LLMs in their projects. With an implementation time of just 30 minutes, this skill can quickly integrate into your existing workflows, enhancing productivity and efficiency. One of the key benefits of the prompt-engineer-skill is its ability to save time by simplifying the prompt creation process. By providing a structured approach to developing prompts, users can avoid the trial-and-error method that often consumes valuable hours. This skill is particularly beneficial for those in roles such as AI developers, product managers, and data scientists who frequently work with LLMs and need to produce high-quality outputs quickly. Practical use cases for the prompt-engineer-skill include generating content for marketing campaigns, creating conversational agents, and developing training data for machine learning models. For instance, a product manager can use this skill to create compelling prompts for a chatbot that engages users effectively, while a data scientist might leverage it to produce prompts for data analysis tasks. The versatility of this skill makes it a valuable asset in various AI-first workflows. While the implementation of the prompt-engineer-skill is rated as intermediate, it requires no specialized department knowledge, making it accessible to a wide range of users. As organizations increasingly adopt AI automation and workflow automation strategies, integrating this skill can significantly enhance the quality and efficiency of LLM interactions, ultimately driving better outcomes in AI projects.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/repo-phuocdt/prompt-engineer-skillCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Transform this rough idea into a production-ready prompt for [LLM_MODEL]: [ROUGH_IDEA]. Use [PROMPT_TECHNIQUE] to optimize the prompt. The prompt should be designed for [USE_CASE] in the [INDUSTRY] sector. Ensure it follows best practices for [LLM_MODEL] and includes clear instructions for the AI to follow.
# Production-Ready Prompt for Customer Support Automation **Context**: This prompt is designed to automate customer support responses for a retail company using the GPT-4 model. It employs Chain-of-Thought prompting to ensure the AI understands the context and provides accurate, empathetic responses. **Prompt**: You are a customer support assistant for [COMPANY], a leading retailer in the fashion industry. Your task is to respond to customer inquiries with accuracy, empathy, and professionalism. Use the following information to guide your responses: - **Customer Inquiry**: [CUSTOMER_INQUIRY] - **Product Information**: [PRODUCT_INFORMATION] - **Company Policies**: [COMPANY_POLICIES] **Instructions**: 1. Analyze the customer's inquiry to understand their needs and concerns. 2. Provide a clear, concise, and accurate response based on the product information and company policies. 3. Ensure the response is empathetic and professional. 4. If the inquiry cannot be resolved with the provided information, suggest the next steps the customer should take. **Example Response**: Thank you for reaching out to [COMPANY]. I understand that you have a question about our return policy for the [PRODUCT_NAME] you recently purchased. Based on our company policies, you have 30 days from the date of purchase to return the item for a full refund or exchange. Please ensure the item is in its original condition and packaging. If you have any further questions or need assistance with the return process, feel free to contact our customer support team at [SUPPORT_PHONE_NUMBER] or visit our website at [WEBSITE_URL]. We appreciate your business and are here to help!
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