Extreme General Skill Engine
Project description
XGSE: Extreme General Skill Engine
Overview
- The General Skill Engine is Implementation of Anthropic-Agent-Skills Protocol
- To empower your AI agents with a modular skill framework that supports dynamic skill discovery, progressive context loading, planning, and task execution.
- The Agent Skills Framework implements a multi-level progressive context loading mechanism that efficiently manages skill discovery and execution:
- Level 1 (Metadata): Load all skill names and descriptions
- Level 2 (Retrieval): Retrieve and load SKILL.md when relevant with the query
- Level 3 (Resources): Load additional files (references, scripts, resources) only when referenced in SKILL.md
- Level 4 (Analysis|Planning|Execution): Analyze the loaded skill context, plan the execution steps, and run the necessary scripts
This approach minimizes resource consumption while providing comprehensive skill capabilities.
XGSE Features
- 📜 Standard Skill Protocol: Fully compatible with the Anthropic Skills protocol
- 🧠 Heuristic Context Loading: Loads only necessary context—such as
References,Resources, andScriptson demand - 🤖 Autonomous Execution: Agents autonomously analyze, plan, and decide which scripts and resources to execute based on skill definitions
- 🔍 Skill Management: Supports batch loading of skills and can automatically retrieve and discover relevant skills based on user input
- 🛡️ Code Execution Environment: Optional local direct code execution or secure sandboxed (E2B...) execution, with automatic dependency installation and environment isolation
- 📁 Multi-file Type Support: Supports documentation, scripts, and resource files
- 🧩 Extensible Design: The skill data structure is modularized, with implementations such as
SkillSchemaandSkillContextprovided for easy extension and customization
Run Skill Prerequisites
- If Execution code on localhost with uv command, must install 'pip' in .venv:
source ".venv/bin/activate"
python -m ensurepip --upgrade
- Use E2B Sandbox, must config 'E2B_API_KEY' in env
- Use LiteLLM, must config 'LLM_API_KEY' in env
- Can use OpenSkill download Claude skills to local
Examples
- skill: Run skill on local host or sandbox
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