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@harvenstar/agentclick

v0.2.3

Published

Human-in-the-loop approval UI for AI agents. Review, edit, and approve agent actions in your browser before they execute.

Readme

AgentClick


⚙️ How It Works

Most agents still interact like this:

User → Terminal → Agent → Action

AgentClick adds a review step:

Agent proposes → Browser UI opens → User inspects and edits → Agent executes

This keeps the speed of autonomous agents while adding a human-in-the-loop safeguard before irreversible work.


🤖 Supported Agents

AgentClick works as a skill / plugin for modern AI agents. Any agent that can run local tools, send HTTP requests, and follow skill instructions can integrate with it.

  • Claude Code
  • Codex
  • OpenClaw
  • Custom tool-calling agents

🧩 What It's For

AgentClick extends the agent interaction into a browser UI for tasks like:

  • 📧 email drafting and inbox triage
  • 🖥️ shell commands and risky actions
  • 📋 plans and execution trajectories
  • 🧠 memory review and updates

The goal: keep the speed of terminal agents, but add a real review layer before the agent commits to irreversible work.


✨ Why It Helps

  • Edit before execution — change the draft, command, or payload instead of only approve/reject.
  • Shared visual context — move from raw terminal text to a purpose-built UI.
  • Preference learning — feedback from review is persisted so the agent improves over time.
  • Framework-agnostic — anything that can POST JSON and poll an HTTP endpoint can use it.

🚀 Quick Start

npm install -g @harvenstar/agentclick
agentclick

Then open http://localhost:38173 in your browser.

For remote access from another device:

agentclick --remote

--remote automatically downloads and starts a Cloudflare Quick Tunnel. It prints a public HTTPS URL you can open on your phone or another machine.


🧠 Use It With An Agent

Option A — npm global install (AgentClick already running)

Start AgentClick first (agentclick), then tell your agent:

AgentClick is running at http://localhost:38173. Use it whenever you need a browser review UI — for email triage, risky commands, plans, or memory review.

Option B — working inside the AgentClick repo

If your agent can read local files, point it at the skill router:

Load SKILL.md from this repo, start AgentClick locally, and use it whenever you need a browser review UI instead of only terminal output.

The root SKILL.md routes to the right sub-skill automatically.

For OpenClaw in particular, use a stronger model with solid instruction-following, since the workflow is skill-based and depends on the agent following routing instructions reliably.


🧱 Skill Layout

AgentClick is built around a skill-based architecture. The root SKILL.md acts as a router that directs the agent to the appropriate sub-skill.

| Skill | Path | Purpose | How to Use | |---|---|---|---| | Router | SKILL.md | Entry point that routes the agent to the right review workflow. | Load SKILL.md and use AgentClick UI for review. | | Action Approval | skills/clickui-approve/ | Approve or reject risky actions before execution. | Before deleting those files, show me an approval review in AgentClick UI. | | Code Review | skills/clickui-code/ | Review shell commands, diffs, and code-related actions. | Show me a code review in AgentClick UI before running that command. | | Email Review | skills/clickui-email/ | Review inbox items, drafts, replies, and live email sessions. | Open my inbox in AgentClick UI and let me triage emails. | | Plan Review | skills/clickui-plan/ | Inspect and revise proposed plans before the agent runs them. | Show me the plan in AgentClick UI before you start. | | Trajectory Review | skills/clickui-trajectory/ | Review multi-step runs, mistakes, and resume points. | Show me what you just did in AgentClick UI so I can review the steps. | | Memory Review | skills/clickui-memory/ | Review memory files and memory-management changes. | Open memory management in AgentClick UI and let me pick which files to include. |

In most cases, telling the agent to load the root skill is enough.


🛠️ Development

git clone https://github.com/agentlayer-io/AgentClick.git
cd AgentClick
npm install
npm run dev

Development mode:

  • server: http://localhost:38173
  • web: http://localhost:5173

Production-style single-port serving:

npm run build
npm start

📜 License

MIT