Keep team AI environments consistent with automatic asset synchronization
When you open an AI tool, the skills and rules defined by your team are already applied, preventing confusion caused by individual configuration differences. TeamAI collects team AI assets into a single Git repository, so once a team member initializes it, the latest version updates automatically. There is no need to manually copy files or re-enter settings.
Git repository-based asset management
TeamAI stores the AI components your team uses, such as skills, rules, environment variables, agents, hooks, MCP servers, and models, in a single Git repository. When a team manager updates this repository, team members' AI sessions automatically fetch the latest assets. There is no need to manually copy files or re-enter settings. This is the core mechanism that ensures the entire team works in the same AI environment.
Three layers: execution, context, and improvement
TeamAI structures team AI capabilities into three layers. The first is team execution, which ensures all AI tools operate according to the team's methods through skills, rules, and agents. The second is team context, which helps AI understand the team's context through learning data, codebase graphs, and team wikis; this part is in beta. The third is team improvement, which records usage and session data to ensure continuous improvement of team execution; this is also in beta.
Checking agent-specific support scope
TeamAI supports various AI agents, including Claude Code, Codex, Cursor, CodeBuddy, and GitHub Copilot CLI. The supported features vary slightly depending on the agent. For example, some agents support all features, while others support only specific ones. The README details the support status for each agent in a table. It is important to verify whether the AI tools your team uses are included in this list.
Pre-adoption checks
Before adopting TeamAI, you must verify that the AI agents your team uses are on the support list. You should also check whether team members have permission to push branches to the Git repository and whether the default branch is protected. A team manager initializes the repository with the teamai init command, and team members use the same command to set up their environments. You can install resources at either the project scope or the user scope. It is released under the MIT license, allowing free use.
