customize-agent:prompt-engineering

What problem does it solve?

This Skill solves the challenge of ineffective LLM interactions by providing techniques for crafting prompts and commands that optimize performance, reliability, and controllability.

Core Features & Use Cases

• Prompt Engineering Patterns: Offers advanced techniques like few-shot learning, chain-of-thought prompting, and prompt optimization.
• Template Systems: Builds reusable prompt structures for multi-turn conversations and role-based interactions.
• System Prompt Design: Establishes global behavior and constraints for stable instructions across conversations.
• Best Practices: Provides guidelines on specificity, example usage, testing, and version control.
• Common Pitfalls: Alerts users about over-engineering, example pollution, and other common issues.
• Integration Patterns: Discusses integration with RAG systems and validation techniques.
• Performance Optimization: Focuses on token efficiency and latency reduction.
• Agent Prompting Best Practices: Based on Anthropic's best practices for agent prompting.
• Persuasion Principles: Applies persuasion principles for more effective communication with AI agents.

Quick Start

Use the prompt-engineering skill to optimize your prompts for a specific task, such as "Analyze this bug report and determine root cause."