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Cloud World Model AI Jobs
x402
Cloud World Model AI Jobs is a paid API for AI agents from www.cloudworldmodel.ai, paid per call via x402, $0.001/call, status unknown (last checked 2026-09-14).
Runs AI analysis jobs (explain, troubleshoot, bottleneck analysis, or optimization) on simulated cloud infrastructure without provisioning real resources
Price / call$0.001
Success—
StatusUnknown
How this service works
Simulate AWS, GCP, Azure, OCI, and DigitalOcean cloud infrastructure without provisioning real resources. Built for Canvas Cloud AI learners and agents.
Output
Returns a JSON object containing a unique jobId (UUID), a status field (initially 'pending'), and a createdAt timestamp. The agent must poll or retrieve the job result separately once the async analysis is complete.
Example use cases
Beginner-friendly cloud architecture explanation
“Can you explain what's going on in my Cloud World Model simulation sim-xyz789? I'm new to cloud infrastructure, so please keep it simple and jargon-free.”
Bottleneck analysis for simulated GCP setup
“Analyze the bottlenecks in my Cloud World Model simulation sim-gcp-456 — I want to know what's slowing things down in my simulated GCP setup.”
Optimization recommendations for Azure simulation
“My Cloud World Model simulation sim-azure-789 is running inefficiently. Can you run an optimization analysis and tell me how to improve it?”
Technical details
Endpoint
POSThttps://www.cloudworldmodel.ai/api/ai-jobsWhen to prefer
Choose this endpoint when you need AI-driven analysis of a simulated cloud environment without spinning up real cloud resources — ideal for learning, testing architecture decisions, or debugging hypothetical infrastructure. Prefer this over real cloud provider APIs when cost isolation and safe simulation are priorities, or when targeting Canvas Cloud AI learners who need guided, optionally beginner-friendly explanations.
Side effects
- Missing or invalid simulationId returns an error — simulation must exist before analysis
- Invalid 'type' enum value (must be explain, troubleshoot, analyze_bottlenecks, or optimize)
- 'issue' field required when type is 'troubleshoot' — omitting it causes a validation error
- Payment failure via x402 protocol results in 402 response before job is created
- Job stuck in 'pending' if simulation backend is unavailable or overloaded
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| type | string | Type of AI analysis to run |
| issue | string | Problem description (required for troubleshoot type) |
| beginnerMode | boolean | Return simplified, jargon-free output |
| simulationId | string | ID of the simulation to analyze |
Output
Schema · Response
{
"type": "json",
"example": {
"jobId": "ai-job-uuid",
"status": "pending",
"createdAt": "2024-01-01T00:00:00.000Z"
}
}Tags
x402
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Zero review prompt (fires after every successful call)
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