One-click install
npx skills add https://github.com/julianobarbosa/.claude --skill prompting-julianobarbosa
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Prompting
Source: https://github.com/julianobarbosa/.claude/tree/main/skills/Prompting
Command: npx skills add https://github.com/julianobarbosa/.claude --skill prompting-julianobarbosa

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Prompting standardizes how prompts are generated, optimized, and composed across PAI so downstream skills get consistent, high-signal instructions.

Core Features & Use Cases

  • Meta-prompting standard library: Claude 4.x + context engineering best practices, Fabric patterns, and markdown-first structure.
  • Handlebars-based prompt templates: creates agent briefings, workflow structure, gates, and eval prompts (judge/rubric/test cases/comparisons/reports).
  • Token-efficiency via template extraction: reduces repeated prompt bloat and keeps only the variable content dynamic.
  • Prompt-only output: always returns prompts meant to be used elsewhere (use domain skills for final content).
  • Uses validation and lifecycle hygiene: provides guidance and logging patterns for repeatable workflow execution.

Quick Start

Ask the AI to generate a meta-prompt for an upcoming task by specifying what you want the resulting prompt to accomplish and the target output format.

Frequently Asked Questions about Prompting

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

FAQPage Schema
How do I generate reusable prompt templates for AI workflows?▼

To generate reusable prompt templates, this Skill applies a Claude 4.x prompt engineering framework using Handlebars conventions to produce programmatic, markdown-first prompt text optimized for token efficiency and downstream AI tasks.

What is meta-prompting and how does it structure context engineering?▼

Meta-prompting standardizes how prompts are composed by enforcing markdown-first structure, Handlebars templating, and context engineering best practices, producing prompt-only outputs rather than final answers for consistent downstream execution.

Can I use Handlebars templating to create agent briefings and eval prompts?▼

Yes, Handlebars templating creates agent briefings, workflow structures, and eval prompts including judge, rubric, test cases, comparisons, and reports, extracting static content to keep only variable content dynamic for token efficiency.

What is the best way to reduce token bloat when composing prompts?▼

The best way to reduce token bloat is template extraction, which separates static prompt structure from dynamic variable content using Handlebars conventions, ensuring token-efficient composition across repeated prompt generation tasks.

Does this Skill generate final answers or only prompt text for other systems?▼

This Skill generates only prompt text meant for use elsewhere, not final answers. It produces eval-ready and agent-ready prompts using a standardized framework, requiring domain skills to produce final content.

When should I not use a meta-prompting approach for my AI task?▼

You should not use meta-prompting when you need final content answers directly, as this Skill enforces prompt-only output. Use domain-specific skills instead when your task requires generating final answers rather than reusable prompt structures.