Roycept AI Platform Guide
How Roycept AI turns natural-language prompts into running applications inside isolated student sandboxes.
1. Supported Frameworks & Agent Roles
Roycept AI uses the provider configured by your administrator. Its conversational agent works through your request with project tools:
- PlannerInspects workspace files and creates a structured task plan and dependency list.
- BuilderCreates and edits files via
write_file,edit_file, andinstall_dependencies. - DebuggerCaptures compiler/build errors with
run_buildandinspect_logsfor bounded automated repair. - ReviewerVerifies preview health, syncs the PostgreSQL file index, and records a point-in-time recovery snapshot.
Supported runtimes: Vite + React, Node.js + Express, and Static HTML/CSS/JS.
2. Sandbox Isolation & Security
Every project executes in a dedicated non-root container (UID 1000) with dropped Linux capabilities (cap-drop=ALL), no-new-privileges, a read-only root filesystem, PID limits, and an isolated network namespace.
Outbound network traffic is routed exclusively through an SSRF-filtering egress proxy that blocks private IPv4/IPv6 ranges, loopback, and cloud metadata (169.254.169.254). Live previews are served on a separate subdomain origin so generated student apps can never access Roycept authentication cookies.
3. Student Free Tier Limits & Auto-Suspension
| Resource | Student Free Limit |
|---|---|
| Active Projects | 5 projects |
| Simultaneous Running Sandboxes | 2 sandboxes |
| Per-Sandbox Compute | 0.5 vCPU · 512 MB RAM · 512 MB Workspace |
| Daily AI Usage | 40 agent runs · 150,000 tokens/day |
| Inactivity Suspension | 20 minutes (persistent files preserved) |