Craft effective prompts that get the best results from language models.
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What the file says
# Prompt Engineering Skill
> Craft effective prompts that get the best results from language models.
## Core Principle
Prompts are programming for probabilistic systems. Clear instructions, good examples, and structured output formats dramatically improve results.
## Prompt Anatomy
```
┌─────────────────────────────────────────┐
│ SYSTEM PROMPT (Role & Constraints) │
│ "You are a senior code reviewer..." │
├─────────────────────────────────────────┤
│ CONTEXT (Background Information) │
│ "The codebase uses TypeScript..." │
├─────────────────────────────────────────┤
│ EXAMPLES (Few-Shot Learning) │
│ Input: X → Output: Y │
├─────────────────────────────────────────┤
│ TASK (What to Do) │
│ "Review this pull request for..." │
├─────────────────────────────────────────┤
│ FORMAT (Output Structure) │
│ "Respond in JSON with fields..." │
└─────────────────────────────────────────┘
```
## Prompting Techniques
### Zero-Shot
Direct instruction without examples:
```
Classify this customer feedback as positive, negative, or neutral:
"The product arrived late but works great."
```
…
The line at the top of this page pins the label git:20260728.80a7ab6, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
GET https://markdownregistry.com/api/v1/artifacts/art_db7cybbypbm5le7t
GET https://markdownregistry.com/api/v1/resolve?ref=fabioc-aloha/alex_skill_mall/prompt-engineering
GET https://markdownregistry.com/api/v1/blob/822fd895a68708df90989ae6b83e015f3ac841d7a0c14326eb5990cd3ea3e3bc
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
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