| name | prompt-engineering |
| description | Comprehensive prompting techniques including chain-of-thought, few-shot, zero-shot, system prompts, persona design, and evaluation patterns |
| version | 1.0.0 |
| author | workspace-hub |
| category | ai-prompting |
| type | skill |
| trigger | manual |
| auto_execute | false |
| tags | ["prompting","llm","chain-of-thought","few-shot","zero-shot","system-prompts","personas","evaluation"] |
| related_skills | ["langchain","dspy"] |
| capabilities | ["chain_of_thought","few_shot_learning","zero_shot_prompting","system_prompt_design","persona_creation","structured_output","prompt_templates","evaluation_patterns","iterative_refinement"] |
| tools | ["Read","Write","Bash","Grep"] |
| platforms | ["python","api"] |
| requires | [] |
| scripts_exempt | true |
Prompt Engineering
Quick Start
import openai
client = openai.OpenAI()
response = client.chat.completions.create(
model="gpt-4",
messages=[
{"role": "system", "content": "You are an expert engineer."},
{"role": "user", "content": "Explain mooring systems."}
]
)
print(response.choices[0].message.content)
When to Use This Skill
USE when:
- Designing prompts from scratch for any use case
- Learning core principles applicable across all LLMs
- Need portable patterns not tied to specific frameworks
- Building simple LLM integrations without heavy dependencies
- Optimizing existing prompts for better results
- Creating reusable prompt templates for teams
- Debugging underperforming LLM applications
- Teaching prompt engineering to others
DON'T USE when:
- Need framework-specific features (use LangChain/DSPy)
- Require programmatic optimization (use DSPy)
- Building production RAG systems (use LangChain)
- Need conversation memory management (use frameworks)
Prerequisites
pip install openai>=1.0.0
export OPENAI_API_KEY="sk-..."
pip install anthropic>=0.5.0
export ANTHROPIC_API_KEY="sk-ant-..."
pip install openai>=1.0.0
export AZURE_OPENAI_ENDPOINT="https://..."
export AZURE_OPENAI_KEY="..."
pip install pytest promptfoo
Resources
- OpenAI Prompt Engineering Guide:
