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customize-agent:prompt-engineering

Craft effective prompts and commands for LLM interactions.

98|Updated Jun 14, 2026

Search Tags:#prompt engineering #performance optimization #LLM interaction #template systems #command crafting

One-click install

npx skills add https://github.com/zhuangwenhui/CodingSkills --skill customize-agent-prompt-engineering

Or copy as Structured Prompt for Agent▼

Please help me install this Agent Skill.
Skill: customize-agent:prompt-engineering
Source: https://github.com/zhuangwenhui/CodingSkills/tree/main/prompt-engineering
Command: npx skills add https://github.com/zhuangwenhui/CodingSkills --skill customize-agent-prompt-engineering

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires Anthropic , and includes scripts (resource) and references (resource) components.

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."

Frequently Asked Questions about customize-agent:prompt-engineering

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

What is the best way to optimize LLM interactions for performance and reliability?▼

You can design global system prompts to establish stable instructions and constraints across multi-turn conversations. This Skill provides template systems for role-based interactions and global behavior management.

How do I craft effective prompts and commands for complex tasks?▼

Crafting effective prompts involves applying persuasion principles, specificity guidelines, and few-shot examples. This Skill guides you through command crafting and prompt optimization patterns for complex LLM tasks.

Does this approach work with RAG systems and Anthropic models?▼

Yes, the prompt engineering patterns include integration techniques for RAG systems and agent prompting best practices based on Anthropic's guidelines. This ensures optimized performance within these specific environments.

What are common pitfalls in prompt engineering and how do I avoid them?▼

Common pitfalls include over-engineering prompts, example pollution, and token inefficiency. This Skill alerts you to these issues and provides best practices for testing, version control, and latency reduction.