# Quickstart

> Make your first Rowe API request in a few minutes. Create an API key, send a point cloud or cad_scene to the Responses API, and inspect the typed output, reasoning_scene, and usage metadata.

Source: https://fourechelon.com/docs/quickstart · Machine-readable: https://fourechelon.com/openapi.json · Index: https://fourechelon.com/llms.txt

## Three steps

1. Create an API key in the dashboard and store it server-side.
2. Call the Responses API with a model and spatial input.
3. Read typed outputs, usage, and request_id from the response.

## First call

```bash
curl https://fourechelon.com/api/v1/responses \
  -H "Authorization: Bearer $FOUR_ECHELON_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "rowe-1.0",
    "input": {
      "task_type": "fit",
      "object_id": "case",
      "secondary_id": "shelf",
      "point_cloud_scene": {
        "point_clouds": [
          {
            "object_id": "case",
            "kind": "box",
            "points": [
              { "x": 0, "y": 0, "z": 0 },
              { "x": 1, "y": 0, "z": 0 },
              { "x": 0, "y": 1, "z": 1 }
            ]
          }
        ]
      }
    }
  }'
```

## Response shape

```json
{
  "id": "resp_4e1f45c7ebd1",
  "object": "response",
  "model": "rowe-1.0",
  "output": [
    {
      "type": "fit_result",
      "data": {
        "feasible": false,
        "confidence": 0.2862,
        "explanation": "Transformer multimodal model predicts fit feasibility=false.",
        "reasoning_scene": {
          "schema_version": "reasoning_scene.v2",
          "scene_id": "four-cad-analysis",
          "task_type": "fit",
          "objects": [],
          "relations": [],
          "overlays": [],
          "measurements": [],
          "reasoning_steps": [],
          "suggested_changes": [],
          "issue_regions": [],
          "fit_results": [],
          "comparison_results": [],
          "geometry_changes": [],
          "text_explanation": "The highlighted geometry shows why the fit check failed."
        }
      }
    }
  ],
  "usage": {
    "input_tokens": 42,
    "output_tokens": 29,
    "estimated_input_cost_usd": 0.000042,
    "estimated_output_cost_usd": 0.000116,
    "estimated_cost_usd": 0.000158
  },
  "request_id": "req_..."
}
```