sideload

Compress PAI skill context into portable packets for LLM sessions.

1|Updated Dec 18, 2025
One-click install
npx skills add https://github.com/matt-fell-ai/PAI --skill sideload
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: sideload
Source: https://github.com/matt-fell-ai/PAI/tree/main/skills/Sideload
Command: npx skills add https://github.com/matt-fell-ai/PAI --skill sideload

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Sideload compresses and outputs the core context of any PAI skill, enabling quick transfer of knowledge into other LLM sessions without carrying full manuals.

Core Features & Use Cases

  • Context Extraction: Pulls essential routing, tools, and workflows into a dense packet.
  • Cross-Stack Portability: Move knowledge between Claude, Gemini, and others with minimal payload.
  • Instant Competence: Quickly teach a new agent a skill with minimal setup.

Quick Start

  • pai run Sideload skill "Fabric"
  • pai run Sideload full

Frequently Asked Questions about sideload

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

FAQPage Schema
How do I extract and transfer skill context between different LLM platforms?

Context extraction compresses a skill's essential routing, tools, and workflows into a portable packet you can inject into Claude, Gemini, or other LLM sessions. Sideload reads your skill documentation and tools directory, producing a token-efficient context block ready for cross-platform reuse without manual setup.

Can I quickly onboard a new AI agent with minimal overhead?

Yes. Sideload packages core skill knowledge into a high-density context packet designed for rapid agent competence. Instead of transferring full manuals, you get a compressed instruction set with enumerated tools, enabling instant integration across different LLM platforms.

What's the fastest way to move knowledge from one skill into another LLM session?

Sideload automates knowledge transfer by extracting essential routing and tool definitions into a portable Context Packet. Run it against any skill's documentation and tools directory to generate a condensed, injection-ready block usable immediately in new LLM sessions.

Does sideload work across Claude, Gemini, and other AI platforms?

Yes. Sideload produces cross-stack portable context packets designed for use with Claude, Gemini, and Droid. The compressed format and tool enumeration remain consistent across platforms, enabling seamless knowledge transfer without platform-specific rewrites.

How does context compression reduce payload size for LLM injection?

Context compression extracts only essential routing, workflows, and tool metadata while removing verbose documentation. The result is a token-efficient packet that preserves instruction fidelity and tool availability while minimizing the overhead of injecting skill knowledge into new LLM sessions.