Prompt Engineering Skill
Craft effective prompts that get the best results from language models.
npx skills add majiayu000/claude-skill-registry --skill prompt-engineering-fabioc-aloha-airs-data-analysis --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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." ``` **Best for**: Simple, well-defined tasks the model understands. ### Few-Shot Provide examples to demonstrate the
- Core Principle
- Prompt Anatomy
- Prompting Techniques
- Zero-Shot
- Few-Shot
- Chain-of-Thought (CoT)
- Self-Consistency
- ReAct (Reason + Act)
- System Prompt Patterns
- Role Definition
- Constraint Setting
- Output Format Specification
- Persona + Audience
- Anti-Patterns to Avoid
What does the Prompt Engineering Skill skill do?
Craft effective prompts that get the best results from language models.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill prompt-engineering-fabioc-aloha-airs-data-analysis --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.