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senior-prompt-engineer

Automate prompt design and evaluation for LLM-powered agent workflows.

35|13|Updated Dec 12, 2025
Search Tags:#production#llm#evaluation#patterns#prompt-engineering#agent-design
One-click install
npx skills add https://github.com/wildwasser/opencode-agents --skill senior-prompt-engineer-wildwasser
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: senior-prompt-engineer
Source: https://github.com/wildwasser/opencode-agents/tree/main/.opencode/skills/senior-prompt-engineer
Command: npx skills add https://github.com/wildwasser/opencode-agents --skill senior-prompt-engineer-wildwasser

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill enables production-grade design and optimization of prompts, patterns, and agent-based workflows for robust LLM-powered products.

Core Features & Use Cases

  • Craft and apply proven prompt patterns to improve model performance and reliability.
  • Architect and evaluate end-to-end prompt-driven systems, including RAG, few-shot strategies, and chain-of-thought prompts.
  • Support agent-based orchestration and system design for scalable AI products, including integration with LangChain and similar tooling.
  • Use Case: When building a complex AI product, create a consistent prompt design framework that yields predictable outputs and governance.

Quick Start

Describe a production-grade prompt design plan for a given AI product, including patterns, evaluation steps, and integration with agent-based workflows.

Frequently Asked Questions about senior-prompt-engineer

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

FAQPage Schema
How do I design production-grade prompts for LLM-powered products?▼

Production-grade prompt design applies proven prompt patterns, few-shot strategies, and chain-of-thought techniques to yield predictable, structured outputs and governance for robust LLM-powered products.

What's the best way to evaluate prompt patterns and agent-based workflows?▼

Evaluating prompt patterns and agent-based workflows requires architecting end-to-end prompt-driven systems with robust evaluation steps, testing few-shot strategies, and validating structured outputs for predictable performance.

Can I use chain-of-thought prompts and few-shot strategies with RAG integration?▼

Yes, you can architect and evaluate end-to-end prompt-driven systems that combine chain-of-thought prompts, few-shot strategies, and RAG integration to support complex system architecture and scalable AI products.

Does this approach support agent-based orchestration and integration with common tooling?▼

Yes, it supports agent-based orchestration and system design for scalable AI products, including integration with common tooling like LangChain to build and manage complex agent-based workflows.

Why do I need a prompt design framework for complex AI products?▼

A prompt design framework ensures consistent, predictable outputs and governance across complex AI products by automating the application of proven patterns, structured outputs, and robust evaluation throughout development and production.

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