Set up TeamAI for a new team or join an existing one. The skill guides installation checks, shared resource management, member and role administration, and removal, with diagnostic checks to verify setup.
TeamAI day 0 and repo lifecycle: create a team repo as admin, join an existing team as a member, manage members, roles, MCP and env, and uninstall. Loaded on demand by the teamai discovery stub.
Review the instructions the agent will receive before you install.
You run the commands; the user only makes choices when you ask. They may not know Git — never explain branches, commits or clones.
node --version # must be >= 20
teamai --version # install once with: npm install -g teamai-cli
Then pick the flow. A user setting up a new team becomes its admin and creates
the repo; a user joining an existing team needs a repo URL from their admin. A
would-be member without a URL is still the join flow — join-member.md tells
them how to ask for it. Do not send them to the create-repo flow because the URL
is missing.
| The user wants to… | Load this |
|---|---|
| Set up TeamAI for a team from scratch (create the repo) | {SKILL_DIR}/references/setup-admin.md |
| Join their team, with or without a repo URL | {SKILL_DIR}/references/join-member.md |
| Publish or update skills, rules, MCP, env; invite members; manage roles | {SKILL_DIR}/references/manage-admin.md |
| Remove TeamAI from this machine | {SKILL_DIR}/references/uninstall.md |
| Publish one skill or contribute a doc | "$(teamai skill path core)/references/contribute-member.md" |
| Anything that breaks along the way | "$(teamai skill path core)/references/troubleshooting.md" |
Supported Git providers are Tencent TGit, GitHub, GitLab and CNB;
{SKILL_DIR}/references/setup-admin.md carries the detection probe, the sign-in
and create-repo URLs, and the per-provider caveats, and points at
{SKILL_DIR}/references/provider-tgit.md for everything TGit-specific.
https://github.com/your-org/your-repo). Never the owner/repo short form.--agent to restrict the
install. Let teamai init set up every AI tool already installed (omitting
--agent gives an interactive picker; select all detected tools). After init,
report which agents were set up — in the user's language, which tools now
auto-start TeamAI, which detected tools were skipped and why (e.g. CodeBuddy
design), and any installed hooks that still need trust (e.g. Codex with
automatic trust disabled or unavailable). Verify the real per-tool result with
teamai doctor and teamai hooks list.teamai init does not pull. It saves the config and installs hooks. It does
not copy team skills, rules or MCP. In workspace scope it creates a tool directory
only for a tool named with --agent, or picked when a person runs it in a
terminal. Those resources arrive on that tool's next session start, or when you
run teamai pull. Run from an agent shell (no terminal), a workspace-scope init
without --agent creates no tool directory: the directory appears when the user
opens that tool in the project, and that session start pulls.teamai doctor. Every setup or onboarding flow ends by running
it and resolving what it reports before you call the job done.Every public command and every flag, including the flags --help hides, is listed in
teamai skill get core --full under references/commands.md. Do not guess a flag:
there is no member-invite flag, for instance — inviting happens on the Git
platform's website, as manage-admin.md describes.
In the files below, {SKILL_DIR} is the directory teamai skill path setup prints; a reference file you open on its own writes that directory as SKILL_DIR in braces.
| File | When to load it |
|---|---|
{SKILL_DIR}/references/setup-admin.md | Creating a team repo: provider detection, auth, repo creation, first push. |
{SKILL_DIR}/references/join-member.md | Joining an existing team from a repo URL. |
{SKILL_DIR}/references/manage-admin.md | Day-to-day admin: publishing resources, roles, projects, MCP, env, members. |
{SKILL_DIR}/references/uninstall.md | Removing TeamAI from a machine or from one agent. |
{SKILL_DIR}/references/provider-tgit.md | Tencent TGit: reachability probe, gf install and login, repo creation on init. |
teamai skill get setup --full prints this skill with all five appended.
No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Manage shared team skills, rules, and documents through TeamAI. This skill guides syncing, publishing, checking differences, and diagnosing configuration problems, while directing setup and knowledge-sharing requests to the appropriate workflows.
Turn an AI coding session into a concise team learning document. Summarize the problem, decisions, solution, useful tools, and pitfalls, then publish the Markdown document to the team knowledge base through TeamAI.
Access TeamAI workflows for sharing skills, rules, documents, and environment settings across AI coding tools. This entry skill loads version-matched guidance for team setup, synchronization, codebase knowledge, and sharing lessons from a session.
Turn a large codebase spanning multiple repositories or services into a structured knowledge base. It documents architecture, business rules, and dependencies, links conclusions to source lines, labels confidence in relationships, and supports incremental updates.