repomix-prompt-packet

Generate AI-optimized prompt packets from repository snapshots.

Updated Jun 10, 2025
One-click install
npx skills add https://github.com/Kingly-Agency/kingly-claude-adapter --skill repomix-prompt-packet
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: repomix-prompt-packet
Source: https://github.com/Kingly-Agency/kingly-claude-adapter/tree/main/skills/repomix-prompt-packet
Command: npx skills add https://github.com/Kingly-Agency/kingly-claude-adapter --skill repomix-prompt-packet

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Guides the creation of comprehensive "prompt packets"—AI-optimized repository snapshots paired with engineered prompts and an AI primer.

Core Features & Use Cases

  • Repository snapshot: consolidated codebase context
  • Contextual prompt: tailored queries for the use case
  • AI primer: setup context and guiding principles for the model

Quick Start

Generate a prompt packet for the current repository to support AI-assisted code analysis or documentation.

Frequently Asked Questions about repomix-prompt-packet

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

FAQPage Schema
How do I prepare a repository snapshot optimized for AI code analysis?

Generate an AI-optimized repository snapshot using repomix to consolidate your codebase context. The Skill creates structured prompt packets—snapshots paired with engineered prompts and AI primers—ready to feed into language models for documentation, bug investigation, or architectural planning.

What's the best way to create prompts for AI-assisted code analysis and documentation?

Structure prompts with three components: a repository snapshot capturing code context, a contextual prompt tailored to your use case, and an AI primer setting guiding principles. This layered approach ensures the model receives complete, focused instructions for accurate code analysis or documentation generation.

Can I use prompt packets for onboarding and architectural planning?

Yes. Prompt packets work across multiple use cases including onboarding, architectural planning, and bug investigation. The Skill enforces configuration selection and generates outputs in markdown, XML, or plain text with optional security checks and line-number annotations to suit your workflow.

How do I ensure my repository context is secure and properly annotated for code analysis?

The prompt-packet generation includes optional security checks and configurable line-number annotations. These features let you control which code sections are included and how they're referenced, ensuring sensitive areas are handled appropriately while maintaining precise code locations for AI analysis.

What output formats does prompt-packet generation support?

Prompt packets are generated in markdown, XML, or plain text formats. Choose the format best suited to your downstream AI model or analysis pipeline, with structured outputs that preserve code context and prompt engineering for consistent, reproducible results.

Do I need to manually configure settings to generate prompt packets?

The Skill enforces configuration selection as part of its workflow, guiding you through setup choices before generation. This ensures your prompt packets align with your specific use case—whether documentation, debugging, or architectural review—without requiring manual prompt design.