How does this skill improve AI agent accuracy?

By enforcing direct language, semantic Markdown headers, and specific constraints, it reduces ambiguity and ensures the AI focuses on high-value instructions.

Is this based on official Anthropic documentation?

Yes, this skill is specifically based on Anthropic’s 'Effective Context Engineering for AI Agents' standards and best practices.

What is context engineering?

Context engineering is the practice of curating the most relevant set of tokens during AI inference to maximize performance while minimizing noise and resource usage.

What are the recommended prompt structures?

The skill recommends using clear sections for Background Information, Imperative Instructions, concise Examples, and specific Success Criteria.

Does this skill help reduce token costs?

Yes, it focuses on the 'Progressive Discovery' principle, which avoids massive data dumps in favor of loading detailed information only when needed.

Prompt Engineering Standards

Name: Prompt Engineering Standards
Author: jeffh

byjeffh

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데이터 과학 및 ML

Optimizes AI agent performance using Anthropic-aligned context engineering and prompt structuring principles.

소개

The Prompting skill equips Claude with advanced context engineering capabilities to build more efficient and reliable AI agents. Based on Anthropic best practices, it focuses on maximizing the signal-to-noise ratio within the context window by utilizing progressive discovery, just-in-time information loading, and structured Markdown formatting. It helps developers avoid common pitfalls like verbose explanations or redundant data dumping, ensuring that AI responses are direct, actionable, and cost-effective by treating context as a finite resource.

주요 기능

Standardized Markdown prompt structures
Anthropic-aligned context engineering
Direct imperative language enforcement
Signal-to-noise ratio optimization
8 GitHub stars
Progressive discovery and JIT loading patterns

사용 사례

Establishing consistent prompt formatting for dev teams
Optimizing prompt token usage for improved latency
Designing specialized AI sub-agent architectures

소개

주요 기능

Standardized Markdown prompt structures
Anthropic-aligned context engineering
Direct imperative language enforcement
Signal-to-noise ratio optimization
8 GitHub stars
Progressive discovery and JIT loading patterns

사용 사례

Establishing consistent prompt formatting for dev teams
Optimizing prompt token usage for improved latency
Designing specialized AI sub-agent architectures