senior-prompt-engineer

Solid

World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implementing advanced prompting techniques.

AI & Automation 2,210 stars 164 forks Updated 1 weeks ago Apache-2.0

Install

View on GitHub

Quality Score: 91/100

Stars 20%
100
Recency 20%
90
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Senior Prompt Engineer World-class senior prompt engineer skill for production-grade AI/ML/Data systems. ## Quick Start ### Main Capabilities ```bash # Core Tool 1 python scripts/prompt_optimizer.py --input data/ --output results/ # Core Tool 2 python scripts/rag_evaluator.py --target project/ --analyze # Core Tool 3 python scripts/agent_orchestrator.py --config config.yaml --deploy ``` ## Core Expertise This skill covers world-class capabilities in: - Advanced production patterns and architectures - Scalable system design and implementation - Performance optimization at scale - MLOps and DataOps best practices - Real-time processing and inference - Distributed computing frameworks - Model deployment and monitoring - Security and compliance - Cost optimization - Team leadership and mentoring ## Tech Stack **Languages:** Python, SQL, R, Scala, Go **ML Frameworks:** PyTorch, TensorFlow, Scikit-learn, XGBoost **Data Tools:** Spark, Airflow, dbt, Kafka, Databricks **LLM Frameworks:** LangChain, LlamaIndex, DSPy **Deployment:** Docker, Kubernetes, AWS/GCP/Azure **Monitoring:** MLflow, Weights & Biases, Prometheus **Databases:** PostgreSQL, BigQuery, Snowflake, Pinecone ## Reference Documentation ### 1. Prompt Engineering Patterns Comprehensive guide available in `references/prompt_engineering_patterns.md` covering: - Advanced patterns and best practices - Production implementation strategies - Performance optimization techniques - Scalability considerations - Se...

Details

Author
foryourhealth111-pixel
Repository
foryourhealth111-pixel/Vibe-Skills
Created
3 months ago
Last Updated
1 weeks ago
Language
Python
License
Apache-2.0

Integrates with

Similar Skills

Semantically similar based on skill content — not just same category

AI & Automation Listed

senior-prompt-engineer

World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implementing advanced prompting techniques.

335 Updated today
aiskillstore
AI & Automation Solid

senior-prompt-engineer

World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implementing advanced prompting techniques.

27,705 Updated today
davila7
AI & Automation Solid

prompt-engineer

Writes, refactors, and evaluates prompts for LLMs — generating optimized prompt templates, structured output schemas, evaluation rubrics, and test suites. Use when designing prompts for new LLM applications, refactoring existing prompts for better accuracy or token efficiency, implementing chain-of-thought or few-shot learning, creating system prompts with personas and guardrails, building JSON/function-calling schemas, or developing prompt evaluation frameworks to measure and improve model performance.

9,537 Updated 1 weeks ago
Jeffallan
AI & Automation Solid

senior-prompt-engineer

This skill should be used when the user asks to "optimize prompts", "design prompt templates", "evaluate LLM outputs", "build agentic systems", "implement RAG", "create few-shot examples", "analyze token usage", or "design AI workflows". Use for prompt engineering patterns, LLM evaluation frameworks, agent architectures, and structured output design.

16,782 Updated 3 days ago
alirezarezvani
AI & Automation Solid

prompt-engineer

Expert in designing effective prompts for LLM-powered applications. Masters prompt structure, context management, output formatting, and prompt evaluation. Use when: prompt engineering, system prompt, few-shot, chain of thought, prompt design.

27,705 Updated today
davila7