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writing-prompts

Structure prompts with a five-layer Role, Context, Task, Constraints, and Output framework.

111|29|Updated Mar 25, 2026
Search Tags:#workflow#llm#few-shot#prompt-engineering#system-prompt#instruction-design#layered-prompts
One-click install
npx skills add https://github.com/xiaolai/nlpm-for-claude --skill writing-prompts-xiaolai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: writing-prompts
Source: https://github.com/xiaolai/nlpm-for-claude/tree/main/skills/nlpm/writing-prompts
Command: npx skills add https://github.com/xiaolai/nlpm-for-claude --skill writing-prompts-xiaolai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Universal prompt engineering for any LLM to improve clarity, consistency, and outcomes by focusing on role, context, task, constraints, and output.

Core Features & Use Cases

  • Five-layer framework (Role, Context, Task, Constraints, Output) to structure prompts.
  • Guidance for building robust system prompts, agent prompts, and configuration prompts.
  • Practical templates and examples that map real-world tasks to repeatable prompts.

Quick Start

Follow the five-layer framework to craft deterministic, reusable prompts for any LLM.

Frequently Asked Questions about writing-prompts

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I structure system prompts for LLMs to improve output consistency?▼

Structure system prompts using a five-layer framework: Role, Context, Task, Constraints, and Output. This structured prompt engineering approach ensures deterministic, reusable LLM outputs across various domains.

What is the best way to design few-shot examples for prompt engineering?▼

Design few-shot examples by mapping real-world tasks to repeatable templates within the Task and Output layers. This structured instruction design provides explicit evaluation criteria for any LLM workflow.

Can I use layered prompts to define agent roles and output formatting?▼

Yes, layered prompts explicitly handle role definitions and output formatting. By separating Role, Context, and Constraints, you build robust agent prompts and configuration prompts for any LLM.

How do I create reusable prompt templates for different LLM workflows?▼

Create reusable prompt templates by applying the five-layer structure to standardize role definitions, task instructions, and output formats. This framework maps real-world tasks to repeatable prompts.

Why do my LLM prompts produce inconsistent results across different domains?▼

Inconsistent LLM results often stem from unstructured prompts lacking explicit constraints and evaluation criteria. Applying a layered prompt framework with defined context and task instructions improves clarity and outcomes.

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