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Prompt Engineering Patterns

Skill Verifiziert Aktiv

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.

Zweck

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production environments.

Funktionen

  • Few-shot learning with example selection strategies
  • Chain-of-Thought prompting for step-by-step reasoning
  • Structured outputs using Pydantic for reliable parsing
  • Prompt optimization workflows and A/B testing
  • Template systems for reusable and modular prompts
  • System prompt design for specialized AI assistants

Anwendungsfälle

  • Designing complex prompts for production LLM applications
  • Optimizing prompt performance, consistency, and token usage
  • Implementing structured reasoning and few-shot learning
  • Building reusable prompt templates and system prompts
  • Debugging and refining prompts for improved LLM outputs

Nicht-Ziele

  • Providing pre-built prompts for specific LLM tasks (focuses on patterns)
  • Interacting directly with LLM APIs (demonstrates patterns)
  • Managing LLM infrastructure or deployment

Installation

Zuerst Marketplace hinzufügen

/plugin marketplace add wshobson/agents
/plugin install llm-application-dev@claude-code-workflows

Qualitätspunktzahl

Verifiziert
95 /100
Analysiert 1 day ago

Vertrauenssignale

Letzter Commit3 days ago
Sterne35.3k
LizenzMIT
Status
Quellcode ansehen

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