Tencent/Teamai-CLI: Make Every Team AI Native

Tencent has released TeamAI-CLI, an open-source command-line tool that synchronizes team skills, rules, MCP configurations, and knowledge across multiple AI coding agents including Claude Code, Codex, CodeBuddy, WorkBuddy, OpenCode, Cursor, and Qoder. The tool, installable via `npm install -g teamai-cli`, uses a shared Git repository to distribute resources through a push-review-pull workflow, aiming to make every AI agent operate according to team standards.

TeamAI manages your team's skills, rules, MCP, and knowledge across Claude Code, Codex, CodeBuddy, WorkBuddy, OpenCode, Cursor, Qoder, and other AI agents. npm install -g teamai-cli Create a shared-experience repo on your git host GitHub, GitLab, GitCode, CNB, TGit, or a private Git service , grant write access to team members , then run teamai init https://github.com/yourorg/yourrepo . No team repo yet? Start from a template pre-loaded with production-ready skills, rules, and review agents. Browse the teamai-hub https://github.com/teamai-hub org, click Use this template , then teamai init against your new repo. Choose one, depending on where you want resources installed Project-scope init default, resources installed under the project directory cd /path/to/my-project teamai init https://github.com/yourorg/yourrepo Or, user-scope init resources installed under ~/ teamai init https://github.com/yourorg/yourrepo --scope user Once initialized, every AI session automatically pulls the latest skills / rules and other Harness updates published by admins — no manual sync needed. Full usage guide: docs/usage-guide.md /Tencent/teamai-cli/blob/main/docs/usage-guide.md 中文版 /Tencent/teamai-cli/blob/main/docs/usage-guide.zh-CN.md — covers everything from team creation to day-to-day use. Team Execution × Team Context × Team Improvement : | Layer | Job | In this CLI today | |---|---|---| | Team Execution | Make every agent work the team's way | init / pull / push , skills, rules, agents, hooks, MCP, env | | Team Context | Make every agent understand the team | recall, learnings, codebase graph, teamwiki... | | Team Improvement | Make every execution improve the team | friction-based share-learnings, sessions, digest, dashboard... | | Agent | Team Execution | | | | | | | Team Context | | | Team Improvement | | | |---|---|---|---|---|---|---|---|---|---|---|---|---|---| | | skills | rules | docs | env | agents | hooks | mcp | learnings | codebase | teamwiki | usage | sessions | dashboard | | Claude Code | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | | Codex | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | | Cursor | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | | Qoder | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | | CodeBuddy | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | | OpenCode | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | — | — | — | | WorkBuddy | ✓ | ✓ | ✓ | ✓ | — | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ | | OpenClaw | ✓ | ✓ | ✓ | ✓ | — | — | — | ✓ | ✓ | ✓ | — | — | — | | Hermes | ✓ | — | ✓ | ✓ | — | — | — | ✓ | ✓ | ✓ | — | — | — | | DeepSeek Harness | ✓ | — | ✓ | — | — | — | — | ✓ | ✓ | ✓ | — | — | — | Git providers — GitHub · GitLab · GitCode · CNB · TGit · private Git service. Team-wide settings an admin configures once and delivers to every member on teamai pull : | Capability | Command | What it does | |---|---|---| | Roles | teamai roles | Define role → namespace mappings so each member syncs only the skills for their role. | | Tags | teamai tags | Tag skills / rules so members subscribe to just the tags they need. | | Sources | teamai source | Subscribe to additional skill repos — other teams' public repos, or shared/public repos within your own org; subscribed skills sync automatically on pull. | One Team. One Harness. Every Agent. TeamAI keeps skills, rules, docs, and hooks in a shared git repo and distributes them to every member's local AI tools through a "push → review & merge → pull" flow — with support for subscribing to other teams' or shared repos' Harness. teamai push → create branch + MR → reviewer approves + merges ↓ SessionStart hook → teamai pull → synced to local AI tools Members push changes via teamai push , which opens a Merge Request for review. Re-running teamai push on a resource that is still waiting in an unmerged PR updates that PR in place instead of opening a duplicate. Once merged, teamai pull triggered automatically on session start via the SessionStart hook syncs the latest resources locally. Skills sync to ~/.claude/skills/ , ~/.codex/skills/ , ~/.cursor/skills/ , ~/.codebuddy/skills/ , etc. In a project-scope install, SessionStart first creates that tool's project root e.g. <project /.claude if it is missing, then pulls into it — a bare teamai pull still will not invent agent directories. Declare custom hooks in hooks/hooks.yaml and teamai pull delivers them to every AI tool: hooks: - id: block-secret description: Scan for secrets before commit event: PreToolUse matcher: Bash command: 'bash -lc "~/.teamai/team-scripts/scan-secret.sh" || true' tools: claude, cursor teamai hooks list list effective hooks teamai hooks inject re-reconcile into every installed tool teamai hooks remove remove all teamai-managed hooks Declare once in mcp/mcp.yaml ; teamai pull writes each tool's native config. Use ${VAR} for secrets. servers: - name: gpu-analysis transport: http stdio | http | sse url: https://example.com/api/mcp headers: Authorization: Bearer ${GPU ANALYSIS TOKEN} teamai mcp list | inject | remove Subscribe to additional skill repos — other teams' public repos, or shared/public repos within your own org: teamai source add https://github.com/other-team/teamai-public.git --name other-team teamai source list teamai source browse other-team browse available skills teamai source remove other-team The add/remove change takes effect locally right away, and subscribed skills sync on the next teamai pull . Run teamai push when you want to share the teamai.yaml change with teammates. Share and restore the team's npm packages and Claude Code plugins: teamai install typescript teamai install typescript@5.9.2 --npm teamai install code-review@claude-plugins-official teamai push Share the declarations teamai install Install everything declared by the team See the Usage Guide /Tencent/teamai-cli/blob/main/docs/usage-guide.md team-packages for the complete workflow and configuration. Every agent understands how the team works. Beyond distributing the Harness, TeamAI organizes accumulated team experience and code structure into a searchable knowledge base that the AI recalls automatically when needed. When a session ends, the Stop hook scores it by friction — signals that the session hit something worth remembering: you interrupted or corrected the AI, denied a tool call, or the AI had to retry failing tools. A long-but-routine session lots of tool calls, no friction does not trigger; a session where you actually fought a problem does. If the score is high enough, the AI suggests: teamai This session may contain a problem worth documenting: you interrupted the AI twice, the AI retried failing tools 8 times. Task: Fix duplicate project-level Hook injection Consider running /teamai-share-learnings to summarize what you learned and share it with your team. The hint names the non-zero friction signals that triggered it and, when available, includes a redacted, single-line summary of the first task. The /teamai-share-learnings skill summarizes the session and pushes a learning document directly to the team repo. Each session is prompted at most once. Let the AI automatically search accumulated team knowledge before a task. This feature is off by default and must be enabled explicitly — teams can set sharing.recall.enabled: true in teamai.yaml as the default, and members can override locally: teamai recall enable on: deploy the teamai-recall subagent + inject guidance rules teamai recall disable off: remove the subagent and rules teamai recall status show effective state team default + user override Search runs via a subagent : once enabled, teamai pull deploys the built-in teamai-recall subagent into each AI tool's agents/ directory. The AI invokes it before a task — the subagent extracts keywords, runs the search, reads the matched source files, and returns a structured summary of team knowledge. The subagent first runs a relevance precheck teamai recall --check and skips retrieval entirely when the task is unrelated to team knowledge. Under the hood it shells out to the teamai recall command, which you can also run manually: bash $ teamai recall "port conflict" 1/2 MR review caught a port-conflict bug ★1 user Author: member-a | Score: 18.5 | Tags: troubleshooting, networking 2/2 Deployment configuration best practices project Author: member-b | Score: 12.0 | Tags: deploy, config Matched: conflict | Missing: port teamai import parses source repos into a structured graph under teamwiki/ , enabling structurally-aware retrieval: teamai import --from-repo https://github.com/org/repo teamai import --from-org myorg batch import all repos teamai codebase --lint health check The graph stores components, interfaces, configs, and cross-repo import edges. teamai recall uses it for graph-boosted re-ranking. When a recall hit comes from a codebase page, the result includes a Sources: line listing the relevant source file paths — giving agents a direct starting point for code changes instead of re-exploring the repo. Edges come from two tracks that run together, with AST results taking precedence on overlap: - AST track TypeScript/JavaScript, Python, Go : a WASM tree-sitter https://tree-sitter.github.io/ parser resolves import / require , call sites, and TS implements clauses to precise file-to-file DEPENDS ON / REFERENCES / IMPLEMENTS edges tagged code-ast , with confidence weights . - Heuristic track all languages, including Java/Rust : regex-based extraction tagged code-heuristic , which also covers languages the AST track does not. The WASM parser is a pure-JavaScript dependency — no native toolchain is required. If it fails to load for any reason, extraction falls back to the heuristic track and records an AST UNAVAILABLE gap. Set TEAMAI SKIP AST=1 to force heuristic-only extraction. Every execution makes the entire team smarter. Insight into how the team actually uses its AI tools, and a starting point for turning session friction into shared skills, rules, and knowledge: | Capability | Command | What it shows | |---|---|---| | Usage | teamai digest | Weekly team digest — token usage, conversation volume, and intervention rate. | | Sessions | teamai session save | Privacy-scrubbed per-session summaries tool sequence, prompt turns, interventions that feed the digest's Session Highlights. | | Dashboard | teamai dashboard | Web dashboard showing team members' live coding-session status, intervention count, and token usage. | | KB Health | teamai dashboard → KB Health | Built-in dashboard page reporting knowledge-base usage & health — coverage by type, top recalled entries, silent entries, recall trend, author contributions, and a maintenance console. | | Command | Description | |---|---| | teamai init | Initialize: OAuth login, link repo, register member, inject hooks | | teamai pull | Pull team resources and inject into local AI tools | | teamai push | Push local resources to a branch and open a Merge Request | | teamai install target | Install declared npm packages and Claude plugins; with a target, also update teamai.yaml | | teamai status | Show local vs team repo diff | | teamai contribute | Share session experience to team repo | | teamai recall <query | Search the team knowledge base BM25 + graph-boost | | teamai recall enable/disable/status | Toggle or check recall state | | teamai recall promote learningId | Promote a high-confidence learning to formal knowledge skills/rules/docs | | teamai recall maintenance | Maintain knowledge base health: prune low-confidence learnings, writeback confidence scores, flag stale entries | | teamai import | Import knowledge --dir , --from-repo , --from-org , --from-repo-list , --from-mr , --from-iwiki | | teamai codebase --lint | Knowledge graph health check | | teamai ci extract-mr --url <url | CI: extract knowledge from MR, post comments, write after merge | | teamai members | List team members | | teamai roles | Manage team roles and namespaces | | teamai tags | Manage tag-based skill/rule filtering | | teamai skill exclude add/remove/list | Manage skills excluded from local sync usage guide /Tencent/teamai-cli/blob/main/docs/usage-guide.md excluding-skills-you-dont-need | | teamai source | Manage skill subscription sources other teams or your org's shared repos | | teamai remove <type <name | Remove a resource and open MR | | teamai session save | Record a privacy-scrubbed session summary to a monthly log --push feeds digest | | teamai digest | Generate weekly team usage digest | | teamai doctor | Diagnose configuration issues | | teamai uninstall | Remove all teamai resources and hooks | PRs are welcome Please read CONTRIBUTING.md /Tencent/teamai-cli/blob/main/.github/CONTRIBUTING.md first.