TeamAI-CLI: Empowering Teams to Become AI Native with a Git-Based Foundation

Summary

TeamAI-CLI, developed by Tencent, is a powerful command-line interface aimed at making every team AI native. It offers a unified, Git-based platform for teams to collaborate, learn, and continuously improve with AI. This tool transforms individual AI capabilities into shared team assets, integrating AI agents, machines, and team members for enhanced efficiency.

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Introduction

TeamAI-CLI, developed by Tencent, is an innovative command-line interface designed to empower development teams by making them AI native. It provides a common foundation for teams to work, learn, and continuously improve with artificial intelligence. By transforming individual AI capabilities into shared team assets, TeamAI-CLI facilitates the utilization of AI across agents, machines, and team members.

Why Use It and Key Benefits

TeamAI-CLI addresses the challenge of integrating AI effectively into team workflows, offering a robust Git-based platform. It builds three layers of capabilities:

Team Execution: Enables all agents to operate according to team standards, managing skills, rules, documentation, environments, agents, hooks, MCP, and models.
Team Context (beta): Helps all agents understand the team through shared learnings, code knowledge graphs, and a team wiki.
Team Improvement (beta): Accumulates every execution as team power, tracking usage, sessions, and providing a dashboard for insights.

This comprehensive approach ensures that AI tools are not just individual aids but integral parts of team collaboration and knowledge sharing.

Installation

To get started with TeamAI-CLI, you can install it globally via npm:

npm install -g teamai-cli

For team administrators or personal use, create a shared repository on your Git host (GitHub, GitLab, etc.) and grant write access to team members. Then, initialize TeamAI:

teamai init https://github.com/your-org/your-repo

Team members can initialize TeamAI within their project directory or globally:

# Project-scope init (default, resources installed under the project directory)
cd /path/to/my-project
teamai init https://github.com/your-org/your-repo

# Or, user-scope init (resources installed under ~)
teamai init https://github.com/your-org/your-repo --scope user

After initialization, updates to skills and rules published by administrators are automatically pulled at the start of an AI session.

Examples

TeamAI-CLI simplifies interaction with AI tools. Here are some quick start examples:

To install and load a TeamAI skill and build your team's TeamAI from scratch, send the following to your AI tool:

teamai skill ?????????: https://github.com/Tencent/teamai-cli/tree/main/skills/teamai , teamai skill ?????????? TeamAI ??????????

Once set up, you can interact with the /teamai skill in your AI tool:

Build your team from scratch:
```
/teamai ???? TeamAI ?????????
```

Join a team:

/teamai ???? TeamAI ???????????? URL ? https://github.com/your-org/your-repo

Share resources with the team (skills, rules, MCP, etc.):
```
/teamai xxx skill ?????????
```
Open the TeamAI dashboard:
```
/teamai TeamAI ???????????
```