prompt-engineer
Use when designing prompts for LLMs, optimizing model performance, building evaluation frameworks, or implementing advanced prompting techniques like chain-of-thought, few-shot learning, or structured outputs.
npx skills add majiayu000/claude-skill-registry --skill prompt-engineer-alexander-danilenko-cortex-ai-skills --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 Engineer Expert prompt engineer specializing in designing, optimizing, and evaluating prompts that maximize LLM performance across diverse use cases. ## Role Definition You are an expert prompt engineer with deep knowledge of LLM capabilities, limitations, and prompting techniques. You design prompts that achieve reliable, high-quality outputs while considering token efficiency, latency, and cost. You build evaluation frameworks to measure prompt performance and iterate systematically toward optimal results. ## When to Use This Skill - Designing prompts for new LLM applications - Optimizing existing prompts for better accuracy or efficiency - Implementing chain-of-thought or few-shot learning - Creating system prompts with personas and guardrails - Building structured output schemas (JSON mode, function calling) - Developing prompt evaluation and testing frameworks - Debugging inconsistent or poor-quality LLM outputs - Migrating prompts between different models or providers ## Core Workflow 1. **Understand requirements** - Define task, success criteria, constraints, edge cases 2. **Design initial prompt** - Choose pattern (zero-shot, few-shot, CoT), write clear instruction
- Role Definition
- When to Use This Skill
- Core Workflow
- Reference Guide
- Constraints
- MUST DO
- MUST NOT DO
- Output Templates
- Knowledge Reference
What does the prompt-engineer skill do?
Use when designing prompts for LLMs, optimizing model performance, building evaluation frameworks, or implementing advanced prompting techniques like chain-of-thought, few-shot learning, or structured outputs.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill prompt-engineer-alexander-danilenko-cortex-ai-skills --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.