From nickcrew-claude-ctx-plugin
Optimizes prompts for LLMs and AI systems with structured techniques, evaluation patterns, and synthetic test data generation. Use when building AI features, improving agent performance, or crafting system prompts.
How this skill is triggered — by the user, by Claude, or both
Slash command
/nickcrew-claude-ctx-plugin:prompt-engineeringThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Craft, test, and iterate prompts that deliver reliable outputs across LLMs. Covers prompt optimization techniques, structured prompt design, synthetic test data generation, and evaluation methodology.
Craft, test, and iterate prompts that deliver reliable outputs across LLMs. Covers prompt optimization techniques, structured prompt design, synthetic test data generation, and evaluation methodology.
| Task | Load reference |
|---|---|
| Prompt techniques and patterns | skills/prompt-engineering/references/techniques.md |
| Synthetic test data generation | skills/prompt-engineering/references/synthetic-data.md |
When creating prompts, always display the complete prompt text in a clearly marked section. Never describe a prompt without showing it. The prompt must be copyable and self-contained.
For every prompt engineering task, produce:
npx claudepluginhub nickcrew/claude-cortexProvides workflows to write, debug, and optimize LLM prompts using few-shot examples, chain-of-thought structuring, system prompts, and templates. Activates for prompt improvement requests.
Crafts and optimizes prompts for LLMs and AI systems using proven patterns (zero-shot, few-shot, CoT, role-playing, constitutional, tree-of-thoughts).
Writes, refactors, and evaluates prompts for LLMs. Use for designing new prompts, chain-of-thought, few-shot learning, system prompts with guardrails, structured outputs, and evaluation frameworks.