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Optimizes LLM prompts by analyzing redundancy, simplifying instructions, and rewriting for reduced token usage, lower costs, and improved performance.
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin ai-ml-engineering-packHow this skill is triggered — by the user, by Claude, or both
Slash command
/ai-ml-engineering-pack:optimizing-promptsThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
Optimize LLM prompts for reduced token usage, lower costs, and improved output quality by identifying redundancies, simplifying instructions, and restructuring for clarity.
Optimizes prompts for LLMs using constitutional AI, chain-of-thought reasoning, and model-specific techniques. Transforms basic instructions into production-ready prompts to improve accuracy, reduce hallucinations, and cut costs.
Optimizes prompts for AI performance via chain-of-thought, few-shot examples, token reduction, RAG integration, and model-specific tuning like GPT-4 or Claude. Activates on improve/refine/engineering requests.
Provides workflows to write, debug, and optimize LLM prompts using few-shot examples, chain-of-thought structuring, system prompts, and templates. Activates for prompt improvement requests.
Share bugs, ideas, or general feedback.
Optimize LLM prompts for reduced token usage, lower costs, and improved output quality by identifying redundancies, simplifying instructions, and restructuring for clarity.
Refine prompts for optimal LLM performance. It streamlines prompts to minimize token count, thereby reducing costs and enhancing response speed, all while maintaining or improving output quality.
This skill activates when you need to:
User request: "Optimize this prompt for cost and quality: 'I would like you to create a detailed product description for a new ergonomic office chair, highlighting its features, benefits, and target audience, and also include information about its warranty and return policy.'"
The skill will:
User request: "Optimize this prompt for better summarization: 'Please read the following document and provide a comprehensive summary of all the key points, main arguments, supporting evidence, and overall conclusion, ensuring that the summary is accurate, concise, and easy to understand.'"
The skill will:
This skill integrates with the prompt-architect agent to leverage advanced prompt engineering techniques. It can also be used in conjunction with the llm-integration-expert to optimize prompts for specific LLM APIs.
The skill produces structured output relevant to the task.