by CronusL-1141
Multi-agent team operating system for Claude Code. 108 MCP tools, 40+ agent templates, 10 lifecycle hooks, 7 pipeline workflows. Persistent teams, structured meetings, task wall, real-time React dashboard. No LangChain/AutoGen — pure CC native integration.
# Add to your Claude Code skills
git clone https://github.com/CronusL-1141/AI-companyLast scanned: 5/30/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-05-30T15:45:49.282Z",
"npmAuditRan": true,
"pipAuditRan": true
}See how AI-company compares with popular alternatives.
AI-company is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by CronusL-1141. Multi-agent team operating system for Claude Code. 108 MCP tools, 40+ agent templates, 10 lifecycle hooks, 7 pipeline workflows. Persistent teams, structured meetings, task wall, real-time React dashboard. No LangChain/AutoGen — pure CC native integration. It has 361 GitHub stars.
Yes. AI-company passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/CronusL-1141/AI-company" and add it to your Claude Code skills directory (see the Installation section above).
AI-company is primarily written in Python. It is open-source under CronusL-1141 on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh AI-company against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
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Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
AI Team OS is a shared operating layer for Claude Code and Codex. Keep tasks, project memory, reports and team messages in one place, and follow work across sessions in one Dashboard. Each host keeps its native agent tools; the OS provides the durable record that makes their work understandable and reusable.
🤝 Codex is supported. Use Codex or Claude Code on its own, or connect both to the same OS task wall, project memory, reports, channels and Dashboard. Codex uses its own MCP and hook configuration; native agent tools, host settings and hook trust remain separate. See the installation and capability sections below for the per-host setup and boundaries.
⚡ v1.13.1 - The standby guard becomes a switch you control, and CI stops hiding its own failures.
/os-watcherturns off both the standby reminder and the stop-time block in one place, and releases through a distinct audit branch rather than blending into a normal allow. The Codex counter now waits long enough for the write lock, so a contended machine no longer drops invocation records (48-way concurrency now covered by a test). An oversized test parameter had been truncating the CI log at 54% for every run, hiding any failure past that point - now pinned to a short id. See the changelog for details.Full version history: CHANGELOG.md
116 MCP tools · 212 REST endpoints · 23 dashboard pages · 25 agent templates · 42 ecosystem research tools · 21 machine-checked invariants
A session can end without taking the team's context with it. Tasks, memos, decisions and reports remain available to the next authorized session, whether it runs in Claude Code or Codex.
Parallel agents are useful only when you can tell who owns the work, what actually happened and where to resume. AI Team OS keeps those answers outside any single chat:
The OS records and exposes the work. Your chosen host runs the agents, and you decide what they are authorized to do.
You set the scope. Each root session has its own Leader. A Claude Leader and a Codex Leader can contribute to the same project without pretending to be the same process or sharing host configuration.
Claude Code's installed hooks can supply startup briefings and direction-layer context automatically. Codex can read the same records through MCP, with its own adapter handling supported observations. The OS does not replace either host's scheduler, permissions or agent lifecycle.
Shared project records and channels connect sessions while execution stays native to each host:
Claude Leader and Codex Leader explicitly. Native Codex children join the parent team instead of becoming extra Leaders.busy evidence drives the current roster; waiting, closed and stale records remain available as history. Unknown source or model information stays unknown.channel_send, channel_read and channel_wait for explicit communication. A pending wait can return new messages; it does not restart an ended Codex turn.Keep team preferences and task evidence available across sessions, without relying on a single chat's remaining context.
supersedes and auditable invalidation rather than deletion. Writes are scanned for invisible characters, instruction-override patterns and credential shapes. Claude Code's SessionStart and SubagentStart hooks inject this context; Codex retrieves the shared records through its configured tools.task_memos ledger): task-level execution memos promoted to a dedicated table (row IDs / invalidation axis / quality score / scope_path), recalled on demand via pure-Python BM25 Chinese retrieval; 123 legacy memos backfilled with zero loss.memory_reconcile): zero-LLM BM25 candidate clustering, then merge / invalidate / score / distill on agent confirmation — "the agent computes, the tool persists", with no background resident process introduced.Surfaces: MCP memory_add / memory_list / memory_invalidate / memory_search / memory_reconcile_candidates / memory_reconcile_apply.
Choose the MCP surface for each client instead of loading every capability into every session.
AITEAM_TOOLSETS group switch: 16 capability-domain toolsets; a startup env var decides which modules register. default core profile = task/team/memory/infra/reports (29 tools, hard cap <=50), with incremental default,ecosystem — fits non-CC clients that cap tool counts.AITEAM_READONLY read-only profile: an orthogonal overlay that strips every write tool by explicit allowlist and keeps only read tools — ideal for audit / observer sessions.disallowedTools entries for destructive OS tools (delete project, delete team, restart API). These are declarations in the template; whether the host enforces them depends on the Claude Code version and permission mode. Codex uses its own native permission controls rather than interpreting CC template fields.The OS does not intercept CC's built-in ultracode/Workflow — it becomes its persistent governance layer. Every Workflow run is automatically tracked into the OS, with no manual team setup:
workflow-<wf_id>) the moment it starts/workflows: a live feed of run cards, a phase swimlane timeline, and per-agent telemetry — tokens / duration / status / tool-call counts, advancing live via incremental journal tailing while a run executesaudit:sourceA) instead of idsworkflow_list (browse runs), workflow_get (full ar