clawdis
Skills for the OpenClaw personal AI assistant, covering browser automation, routing requests to coding agents, presenting canvas widgets, running apps on temporary machines, and sharing diffs.
Orchestrates teams of AI agents to run work like a company, with a Node.js server and React UI. Adds skills for delegating tasks, following up on results, reviewing team status, and managing Paperclip tasks from Hermes.
Claude Code
$ npx -y skills add paperclipai/paperclip --agent claude-code
Codex
$ npx skills add paperclipai/paperclip -a codex
Cursor
$ npx skills add paperclipai/paperclip -a cursor
Gemini CLI
$ npx skills add paperclipai/paperclip -a gemini-cli
GitHub Copilot
$ npx skills add paperclipai/paperclip -a github-copilot
OpenCode
$ npx skills add paperclipai/paperclip -a opencode
Windsurf
$ npx skills add paperclipai/paperclip -a windsurf


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Open-source orchestration for teams of AI agents.
If OpenClaw is an employee, Paperclip is the company.
Paperclip is a Node.js server and React UI that orchestrates a team of AI agents to run a business. Bring your own agents, assign goals, and track work and costs from one dashboard. Choose models and harnesses per agent while keeping your team's tasks, skills, permissions, and history in one place.
It looks like a task manager. Under the hood: org charts, budgets, governance, goal alignment, and agent coordination.
Manage business goals, not pull requests.
| Step | Example | |
|---|---|---|
| 01 | Define the goal | "Build the #1 AI note-taking app to $1M MRR." |
| 02 | Hire the team | CEO, CTO, engineers, designers, marketers — any bot, any provider. |
| 03 | Approve and run | Review strategy. Set budgets. Hit go. Monitor from the dashboard. |
If it can receive a heartbeat, it's hired.
Custom processes, HTTP endpoints, and external adapter packages extend the roster. See the adapter overview for setup and capabilities.
Four things have to work for an organization of AI agents to actually produce: the tasks, the org, the training, and the infrastructure. Paperclip is built around exactly those four pillars.
| Pillar | Built for | What it covers |
|---|---|---|
| Agentic Task Manager — Declare intent. Agents work. You verify the output. | Everyone, daily | Tasks, approvals & review gates · proactive agent coworkers · auditable routines & workflows · verify from diffs, screenshots & tests |
| Org Chart for Agents — Roles, permissions & boundaries for humans and agents. | Managers | Mixed human + agent org chart · responsibilities, delegation, specialization · governance: who can do what · scoped secrets & company boundaries · connection permissions & responsible-user identities |
| Agent Employee Training — Design, train & evaluate your AI employees. | Enablers | Skill Studio & shared org-wide skills · evals & saved test runs · active learning loops & quality metrics · performance reviews for agents · saved test inputs · skill version history & restore · reusable team templates |
| Agentic OS — The infrastructure that makes the work run. | IT & platform | Cross-provider runtime: any model, any agent · sandboxing, integrations & MCP servers · SSO, GRC, RBAC & cost controls · data privacy, internal trace collection, compounding data value · personal & shared app connections · run history & opt-in tracing |
Experimental Agent Chat and chat/email connectors add conversations with agents in Paperclip and through configured services such as Slack, Discord, Telegram, and AgentMail. Enable the relevant instance settings to try them.
Skills for the OpenClaw personal AI assistant, covering browser automation, routing requests to coding agents, presenting canvas widgets, running apps on temporary machines, and sharing diffs.
Gives Claude Code users skills to drive Orca-managed worktrees, terminals and the embedded browser through the orca CLI, plus Jira and Linear ticket work and inline HTML chat visuals. Covers chart, table and mockup output.
Organizes your AI agents for round-the-clock operation, with tools to hire, schedule and report on your agent team. Lets you oversee the agents without staying online yourself.
Gives Claude Code and Codex a coordination layer so multiple AI agents can split up a task, share memory across sessions, and work together instead of running one at a time. Also covers vector search and reinforcement learning for building agents that remember and improve.
Install it with the command on its page. It includes design-guide, delegate-work, follow-up-results. Its skills do not fire on their own yet. Free and open source.
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