SkillNet is an open-source platform designed to treat AI agent skills as first-class, shareable packages, analogous to npm for software development. It offers a comprehensive suite of tools for AI agents to discover, install, create, evaluate, and organize skills, enabling continuous learning and growth from a community-driven ecosystem. The platform targets developers and researchers building sophisticated AI agents that require modular and manageable capabilities.

How It Works

SkillNet standardizes AI agent capabilities as shareable packages, akin to npm for AI. It provides an end-to-end platform for discovering, installing, creating, evaluating, and organizing these skills. The system leverages LLMs for automated skill creation from diverse sources like code repositories, documents, and logs. A novel 5-dimensional quality scoring system (Safety, Completeness, Executability, Maintainability, Cost-Awareness) and a semantic relationship graph help manage and connect skills effectively.

Quick Start & Requirements

Installation is straightforward via pip: pip install skillnet-ai. The system requires Python 3.9+. While basic search and download operations are credential-free, creating, evaluating, or analyzing skills necessitates API keys (e.g., OpenAI, GitHub). Official resources include the project website skillnet.openkg.cn, a technical report arXiv:2603.04448, and Hugging Face integration.

Highlighted Details

• Skill Discovery: Supports keyword and AI semantic search across a curated set of skills.
• Automated Skill Creation: Generates structured skill packages from GitHub repos, documents (PDF, PPT, Word), conversation logs, or natural language prompts using LLMs.
• Comprehensive Evaluation: Scores skills across five dimensions: Safety, Completeness, Executability, Maintainability, and Cost-Awareness.
• Skill Relationship Mapping: Automatically identifies and visualizes connections such as similar_to, belong_to, compose_with, and depend_on between skills.
• OpenClaw Integration: Seamlessly integrates as a built-in skill for the OpenClaw agent, enabling autonomous skill management.

Maintenance & Community

The project encourages community contributions for skills, bug fixes, and feature suggestions, with a dedicated contributing guide available. Specific details on core maintainers, sponsorships, or dedicated community channels (like Discord/Slack) are not explicitly detailed in the provided README.

Licensing & Compatibility

SkillNet is released under the MIT License, which is permissive and generally suitable for commercial use and integration into closed-source projects without significant restrictions.

Limitations & Caveats

The project's technical report is dated 2026, suggesting a recent or forward-looking development status. While specific limitations are not detailed, reliance on LLMs for automated creation and evaluation implies potential costs, latency, and accuracy considerations. The effectiveness of the 5-dimensional quality scoring system would require empirical validation.