🏗️ Architecture: How to implement an OpenClaw-inspired Computer Use Agent sys...

Date: 2026-02-06
Time: 14:42:33 UTC
Session: editor2-93.3
Agent: backend
Confidence: 90%
Status: ✅ Documented

📋 Decision Context

Question:

How to implement an OpenClaw-inspired Computer Use Agent system for GoGrab?

Task: Build OpenClaw-inspired Computer Use Agent System

🎯 Decision Made

Chosen:

6-phase architecture: (1) Foundation—install Playwright, wire TaskRunner dispatch and Vitto browser delegation, (2) Core Computer Use Loop with observe→think→act cycle using Claude Vision API, (3) Expanded Desktop with profile-based configs (dev/standard/restricted), screen capture, process management, (4) Skill System with SkillHandler interface and SkillRegistryService wrapping all services, (5) Proactive Agent with workflow triggers, condition monitoring, webhooks, (6) Security with permission tiers (read_only→standard→elevated→admin), audit trail, and rate limiting

Options Considered:

• No alternatives documented

💭 Reasoning

OpenClaw's architecture centers on the observe→think→act loop with Docker sandboxing, 100+ skills, and messaging platform integration. We adapted this for enterprise GoGrab: (1) leveraged existing BrowserAutomationService and DesktopService instead of rewriting, (2) added coordinate-based actions (click_at, type_text, key_press) needed for vision-based control, (3) created ComputerUseLoopService as the core innovation with Claude Vision API for screenshot analysis, (4) built SkillRegistryService for modular capability discovery, (5) wired everything through existing MCP gateway pattern. Key differentiators over OpenClaw: enterprise audit trails, multi-agent orchestration via Vitto, permission-tiered security, cross-session episodic memory.

📁 Files Involved

• apis/backend-ai-api/src/app/infrastructure/services/computer-use-loop.service.ts
• apis/backend-ai-api/src/app/infrastructure/services/computer-use-audit.service.ts
• apis/backend-ai-api/src/app/infrastructure/controllers/computer-use.controller.ts
• apis/backend-ai-api/src/app/infrastructure/services/skill-registry.service.ts
• apis/backend-ai-api/src/app/infrastructure/services/workflow-trigger.service.ts
• apis/backend-ai-api/src/app/infrastructure/services/condition-monitor.service.ts
• apis/backend-ai-api/src/app/infrastructure/guards/computer-use-permission.guard.ts
• apis/backend-ai-api/src/app/infrastructure/infrastructure.module.ts
• MCP/mcp-gograb-ai/src/tools/gateways/computer-use-gateway.ts
• MCP/mcp-gograb-ai/src/tools/gateways/skill-gateway.ts

🔗 Related

• Decision ID: dev_1770388953374_sngee8u
• Session: 93
• Workspace: editor2

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