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prompt-builder

Guide users through recursive prompt creation with layered architecture and library reuse.

Updated Aug 23, 2026
Search Tags:#prompt engineering#prompt optimization#skill composition#sage protocol#behavior generation#recursive prompting
One-click install
npx skills add https://github.com/sage-protocol/sage-pi-adapter --skill prompt-builder-sage-protocol
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prompt-builder
Source: https://github.com/sage-protocol/sage-pi-adapter/tree/main/.claude/skills/prompt-builder
Command: npx skills add https://github.com/sage-protocol/sage-pi-adapter --skill prompt-builder-sage-protocol

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill streamlines the creation of complex, execution-optimized prompts by guiding users through a recursive discovery and composition process, ensuring prompts leverage existing knowledge and components effectively.

Core Features & Use Cases

  • Recursive Prompt Building: Gathers requirements through progressive dialogue and searches libraries for reusable components.
  • Library-First Composition: Prioritizes referencing existing skills and prompts over creating new content.
  • Layered Prompt Architecture: Organizes prompts into four distinct layers: Identity & Constraints, Directive, Behavior Spec, and Execution Plan.
  • Use Case: When tasked with creating a new prompt for code generation, this Skill will first ask clarifying questions about the desired language, framework, and constraints, then search existing code generation prompts and skills, and finally help compose a new, robust prompt that references the found components.

Quick Start

Use the prompt-builder skill to create a new prompt for generating Python unit tests based on existing code.

Frequently Asked Questions about prompt-builder

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

FAQPage Schema
How do I build execution-optimized prompts for complex code generation?▼

To build execution-optimized prompts, use a recursive methodology involving progressive dialogue, library searching, and layered behavior composition to discover, validate, and persist reusable prompt components.

What is the four-layer prompt architecture for prompt engineering?▼

The four-layer prompt architecture structures prompts into Identity & Constraints, Directive, Behavior Spec, and Execution Plan layers to organize complex directives and optimize execution.

How do I create new prompts by reusing existing skills and components?▼

You can create new prompts by prioritizing library-first composition, which searches existing skill libraries to gather and reference reusable components before generating new content.

What is the best way to validate and persist prompts for future use?▼

The best way to validate and persist prompts is by applying built-in validation checklists to verify execution readiness, followed by utilizing persistence strategies to store the finalized prompt architecture.

Does prompt engineering require dependencies or specific environments to compose prompts?▼

Prompt engineering via this approach requires no external dependencies, relying entirely on internal scripts and references to guide the recursive dialogue and behavior generation process.

When should I use recursive prompting instead of writing a single prompt?▼

Use recursive prompting when creating complex, execution-optimized prompts that require progressive dialogue to gather constraints, search libraries for reusable components, and validate layered behavior specifications.

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