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prompt-engineering

Codify prompting techniques for Claude-based workflows with XML tagging and chain-of-thought patterns.

8|2|Updated Jul 13, 2015
Search Tags:#chain-of-thought#prompts#prompt-engineering#multishot#xml-tags#system-instructions
One-click install
npx skills add https://github.com/tstapler/dotfiles --skill prompt-engineering-tstapler
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-engineering
Source: https://github.com/tstapler/dotfiles/tree/main/.claude/skills/prompt-engineering
Command: npx skills add https://github.com/tstapler/dotfiles --skill prompt-engineering-tstapler

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Prompt design for AI systems is error-prone and time-consuming; this Skill provides a structured approach and best practices to craft effective prompts, prompts templates, and system instructions for Claude-based workflows.

Core Features & Use Cases

  • Structured prompting techniques for reliable outputs across agents, commands, and system prompts.
  • XML-tagger template guidance for clear prompt componentization and reuse.
  • Multishot prompting and chain-of-thought patterns to improve reasoning, debugging, and consistency.

Quick Start

Provide a task-specific, structured prompt template for the current goal and context.

Frequently Asked Questions about prompt-engineering

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

FAQPage Schema
What's the best way to structure prompts for reliable Claude outputs?▼

XML tags componentize prompt instructions for Claude by explicitly separating context, examples, and rules, which improves parsing accuracy and enables reliable template reuse across agents and system instructions.

How do I use multishot prompting and chain-of-thought patterns together?▼

Multishot prompting provides example pairs to guide output formatting, while chain-of-thought patterns structure intermediate reasoning steps, together improving consistency and debugging in complex AI workflows.

When do I need chain-of-thought patterns in prompt engineering?▼

Chain-of-thought patterns are needed when tasks require explicit reasoning or debugging, guiding the AI through intermediate logical steps to improve consistency and reduce errors in complex prompt workflows.

Does prompt engineering work with system instructions and agents?▼

Prompt engineering applies directly to system instructions and agents by codifying prompting techniques, ensuring explicit structure, best practices, and safety considerations are maintained across automated Claude-based workflows.

Why are my prompts producing inconsistent outputs across different agents?▼

Inconsistent outputs often result from unstructured prompts; applying XML tagging for componentization, multishot examples, and explicit system instructions standardizes behavior and enforces safety across agents.

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