prompt-engineering
Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.
npx skills add majiayu000/claude-skill-registry --skill antigravity-prompt-engineering --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 Patterns Advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability. ## Core Capabilities ### 1. Few-Shot Learning Teach the model by showing examples instead of explaining rules. Include 2-5 input-output pairs that demonstrate the desired behavior. Use when you need consistent formatting, specific reasoning patterns, or handling of edge cases. More examples improve accuracy but consume tokens—balance based on task complexity. **Example:** ```markdown Extract key information from support tickets: Input: "My login doesn't work and I keep getting error 403" Output: {"issue": "authentication", "error_code": "403", "priority": "high"} Input: "Feature request: add dark mode to settings" Output: {"issue": "feature_request", "error_code": null, "priority": "low"} Now process: "Can't upload files larger than 10MB, getting timeout" ``` ### 2. Chain-of-Thought Prompting Request step-by-step reasoning before the final answer. Add "Let's think step by step" (zero-shot) or include example reasoning traces (few-shot). Use for complex problems requiring multi-step logic, mathematical reasoning, or when you need to verify the model's t
- Core Capabilities
- 1. Few-Shot Learning
- 2. Chain-of-Thought Prompting
- 3. Prompt Optimization
- 4. Template Systems
- 5. System Prompt Design
- Key Patterns
- Progressive Disclosure
- Instruction Hierarchy
- Error Recovery
- Best Practices
- Common Pitfalls
What does the prompt-engineering skill do?
Expert guide on prompt engineering patterns, best practices, and optimization techniques. Use when user wants to improve prompts, learn prompting strategies, or debug agent behavior.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill antigravity-prompt-engineering --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.