# Open Agent Skills: Cross-Platform AI Coding Assistant Skill Library

> Open Agent Skills is an open-source AI coding assistant skill library designed with a plugin-based architecture, supporting multiple mainstream AI coding tools such as Claude Code and OpenAI Codex. Through a unified skill definition format and agent-agnostic design philosophy, it enables 'write once, use anywhere' for skill content.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-05-06T00:44:43.000Z
- 最近活动: 2026-05-06T02:15:27.745Z
- 热度: 147.5
- 关键词: AI 编程助手, Claude Code, OpenAI Codex, 技能库, 插件系统, 跨平台, Swift
- 页面链接: https://www.zingnex.cn/en/forum/thread/open-agent-skills-ai
- Canonical: https://www.zingnex.cn/forum/thread/open-agent-skills-ai
- Markdown 来源: floors_fallback

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## Open Agent Skills: Cross-Platform AI Coding Assistant Skill Library (Main Thread)

Open Agent Skills is an open-source AI coding assistant skill library with a plugin-based architecture. It supports mainstream tools like Claude Code and OpenAI Codex. Its core value lies in the agent-neutral design and unified skill definition format, enabling 'write once, use anywhere' for skill content, thus solving the fragmentation problem in the AI coding assistant ecosystem.

## Background: Fragmentation Plight of AI Coding Assistants

With the rapid development of AI coding assistants such as Claude Code, OpenAI Codex, and Gemini CLI, developers face a new fragmentation issue: each tool has its own skill/plugin system, but skills cannot be reused across tools. For example, a skill written for Claude Code can't be directly used in Codex, leading to redundant work. Open Agent Skills was created to address this problem.

## Core Design Philosophy of Open Agent Skills

### Agent-Neutral Skill Content
The core principle is that skill content should be agent-neutral, while tool-specific guidance is placed in entry point files instead of shared content. This means core knowledge (e.g., Swift performance optimization, IPC communication) is defined once, and tool-specific loading/configurations are handled in their entry points. Adding support for new tools only requires new entry points without rewriting skills.

### Plugin & Skill Hierarchy
The project uses a two-level structure: 
1. **Plugin**: A collection of skills around a specific theme (e.g., Swift development, credential management).
2. **Skill**: A self-contained reference document loaded by compatible assistants when user queries match trigger descriptions. This modular design allows developers to install and use specific plugins as needed.

## Supported AI Tools & Existing Plugins

### Supported AI Tools
- **Claude Code**: Supports via `.claude-plugin/marketplace.json`.
- **OpenAI Codex**: Supports via `.agents/plugins/marketplace.json` and `.codex-plugin/plugin.json`.
- **Gemini CLI**: Support is planned, with discovery format to be determined.

### Existing Plugins
- **Credential Storage**: A local credential management solution for AI coding assistants, featuring non-secret index files (0600 permissions), OS keychain storage for actual keys, secure consumption patterns, and pre-commit hooks to prevent sensitive info leaks.
- **Swift Development Skills**: Covers Swift IPC (XPC, shared memory, etc.), performance optimization (method dispatch, ARC, etc.), synchronization (DispatchQueue, Actor, etc.), and testing (Swift Testing framework usage).

## Usage & Contribution Guidelines

### Usage
For Claude Code users:
1. Add market source: `claude plugin marketplace add Tyr0/open-agent-skills`
2. Install plugins: `claude plugin install credential-storage` or `swift-performance`.
For Codex users: Follow Codex's plugin docs to configure market sources and install plugins.

### Contribution
Before submitting PRs:
1. Read ARCHITECTURE.md to understand plugin/skill format specs.
2. Update both Claude and Codex market registries when introducing new plugins.
3. Keep skill content agent-neutral—tool-specific guidance belongs to entry points, not shared skills.

## Architecture Advantages & Future Outlook

### Core Problem Solved
Open Agent Skills unifies skill definitions to resolve fragmentation, letting developers focus on skill quality instead of repeating work for each tool.

### Scalability
Adding new AI tools is easy: only new entry points are needed, no changes to existing skills, ensuring backward compatibility.

### Future Possibilities
As the AI coding assistant market matures, Open Agent Skills may become an industry standard, reducing maintenance costs for skill developers and providing consistent experiences for users across tools.

## Conclusion: Towards a Standardized AI Coding Ecosystem

Open Agent Skills represents an important direction in the AI coding assistant ecosystem—moving from fragmentation to standardization, and from redundant work to efficient reuse. Its agent-neutral design and modular plugin architecture offer a win-win solution for developers and tool vendors. As more AI tools emerge, this cross-platform skill sharing mechanism will grow increasingly vital.