Prompting

Generate and validate prompts using Handlebars templates with YAML data.

1|1|Updated Mar 1, 2026
One-click install
npx skills add https://github.com/RooseveltAdvisors/claude-agent-stack --skill prompting-rooseveltadvisors
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Prompting
Source: https://github.com/RooseveltAdvisors/claude-agent-stack/tree/main/skills/Prompting
Command: npx skills add https://github.com/RooseveltAdvisors/claude-agent-stack --skill prompting-rooseveltadvisors

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the complex process of prompt engineering by providing a robust system for generating, validating, and optimizing prompts programmatically.

Core Features & Use Cases

  • Dynamic Prompt Generation: Use Handlebars templates to create prompts based on data, ensuring consistency and reusability.
  • Prompt Validation: Check templates for syntax errors and ensure all necessary variables are present before rendering.
  • Standards Enforcement: Adheres to best practices for prompt engineering, improving AI performance and reliability.
  • Use Case: Automatically generate personalized onboarding prompts for new users based on their role and project requirements.

Quick Start

Use the prompting skill to render the 'Briefing.hbs' template with the data from 'agents.yaml'.

Frequently Asked Questions about Prompting

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

FAQPage Schema
How do I dynamically generate AI prompts using YAML data and Handlebars templates?

Dynamic AI prompt generation uses Handlebars templates populated with YAML data to ensure consistency and reusability. Custom Handlebars helpers enable advanced text manipulation and conditional logic for complex prompt construction.

Can I validate prompt templates for syntax errors and missing variables before rendering?

Prompt validation checks Handlebars templates for syntax errors and ensures all necessary variables are present before rendering. This prevents runtime failures and improves AI performance and reliability during prompt generation.

What is meta-prompting and how does it optimize prompt engineering standards?

Meta-prompting optimizes prompt engineering by programmatically generating and validating prompts against best practices. This approach enforces standards, improving AI reliability and performance through consistent template creation and adherence to established rules.

Does this prompt generation approach work for automating personalized onboarding prompts based on user roles?

Prompt generation supports automating personalized onboarding prompts based on user roles and project requirements. By leveraging YAML data and Handlebars templates, it creates consistent, reusable prompts tailored to specific user contexts.

What's the best way to programmatically create and optimize AI prompts without hardcoding strings?

Programmatic prompt optimization uses a templating system with Handlebars and YAML data to replace hardcoded strings. This method supports template creation, validation, and meta-prompting to dynamically generate text adhering to prompt engineering standards.

How do I use custom Handlebars helpers for advanced text manipulation in AI prompt templates?

Custom Handlebars helpers facilitate advanced text manipulation and conditional logic within AI prompt templates. Combined with YAML data inputs, these helpers allow dynamic prompt generation while maintaining syntax validation and engineering standards.