OpenCrew Team OS
Run a role-based OpenClaw AI team from the chat workspace your team already uses.
What does this agent do, and when should you use it?
OpenCrew is a multi-agent collaboration system built on OpenClaw for decision makers who want to operate an AI team through Slack, Feishu, or Discord. It maps channels or groups to roles and threads to tasks, with workspaces for roles such as CoS, CTO, Builder, CIO, Research, KO, and Ops. Its operating model includes L0–L3 autonomy levels, QAPS task types, structured Closeouts and Checkpoints, knowledge extraction by KO, and change auditing by Ops. Agents can delegate work through `sessions_send`; on Slack, a separately configured Slack App enables @mention-based Discussion collaboration. It is deployed into an existing OpenClaw installation with connected chat platforms, rather than offered as a standalone hosted service.
During deployment, OpenCrew adds role workspaces and the shared protocols under shared/ to an OpenClaw setup, then configures channel-to-agent routing in openclaw.json. Users start work in channels such as #hq, #cto, and #build, or their equivalent groups, while each agent responds within its assigned domain and organizes tasks in threads. Delegation uses a visible channel anchor plus sessions_send as a two-step handoff. In Slack Discussion mode, an orchestrating agent with an independent Slack App joins an execution channel and collaborates through @mentions in the same thread. Work can produce Closeouts, Checkpoints, and reusable knowledge distilled by KO; system changes are subject to an Ops review loop.
- An existing OpenClaw user who wants separate Slack channels for executive intent, technical design, and implementation handled by CoS, CTO, and Builder roles.
- A decision maker managing several concurrent initiatives who wants channels to show responsibilities and threads to keep each task separate.
- A Slack team that needs a coordinator and an execution agent to discuss, review, and reach agreement in a shared task thread.
- A user who wants project learnings compressed into structured Closeouts and later distilled into reusable operating knowledge by KO.
- An OpenClaw user on Feishu or Discord who wants the same role-per-channel operating model while accepting platform-specific limitations.
What are this agent's strengths and limitations?
- Uses a concrete channel/group-to-role and thread-to-task model, making team responsibilities and work visible in the chat workspace.
- Offers both Delegation and Slack Discussion A2A modes; the latter supports review and discussion by independently identified bots in execution channels.
- Combines structured Closeouts, Checkpoints, three-layer knowledge capture, and Ops Review in one operating model.
- Supports Slack, Feishu, and Discord, with a documented three-role starting configuration of CoS, CTO, and Builder.
- Core operation depends on OpenClaw, so it is not a standalone general-purpose multi-agent runtime.
- The documented, validated Discussion mode is Slack-specific and requires an additional Slack App plus multi-account configuration.
- A2A @mention checks, turn counting, and `NO_REPLY` discipline are prompt-enforced; the repository recommends low-risk testing for models other than Claude Opus 4.6.
- Feishu lacks thread task isolation, and Discord Discussion mode is blocked by an OpenClaw code-level bug.
- The model uses more total tokens than a single-agent setup, and Slack’s free tier retains message history for only 90 days.
How do you install or deploy this agent?
Prerequisite: an existing OpenClaw installation for which openclaw status succeeds. Connect Slack, Feishu, or Discord; create #hq, #cto, and #build (or equivalent groups) and invite the bot. Clone the repository with git clone https://github.com/AlexAnys/opencrew.git /tmp/opencrew. Then have the existing OpenClaw follow the repository’s DEPLOY.md incremental deployment flow: provide platform credentials (Slack Bot Token and App Token; Feishu App ID and App Secret; or Discord Bot Token), map channels to CoS/CTO/Builder, and preserve existing models, auth, and gateway settings.
How do you use this agent?
After deployment, send a message in each CoS, CTO, and Builder channel or group to confirm that its assigned agent replies. Ask the CTO to delegate a task to Builder and verify that a response appears in Builder’s channel. For one-way handoffs, configure A2A Delegation with agentToAgent.allow and maxPingPongTurns, then add the Delegation rules to the participating roles. For Slack discussion collaboration, create an independent Slack App for at least one key agent, configure multiple accounts while retaining accounts.default, invite the new bot into the target channel, and verify that both agents reply to @mentions in one thread.
How does this agent compare with similar options?
The repository distinguishes OpenCrew from developer SDKs such as CrewAI and AutoGen: those are presented as code-based agent orchestration tools, while OpenCrew is positioned around managing an AI team through Slack with explicit roles, tasks, knowledge capture, and governance.