Live Jev API debugger

Inspect the decision before your agent acts.

Run Jev through OmniaKey with a workflow preset or your own native decision contract. Edit the JSON input and inspect the model’s actual answers, probabilities, and token usage. Your OmniaKey API key stays in memory and is never saved.

Choose a workflow preset and provide the task context. The preset defines bounded Jev questions, evaluates your input through OmniaKey, and returns the model’s original answers. Open the native request preview to inspect what will be sent.

OmniaKey API key

Used only for this request. The page does not persist the key.

Request endpoint

https://api.omniakey.com/v1/alpha/search

All presets use OmniaKey’s native Jev endpoint with the jev-latest model.

Workflow preset input

{
  "task": "Review a complex customer dispute with 100k context and tool use",
  "candidates": [
    {
      "id": "fast-model",
      "description": "Fast general model with 32k context",
      "cost": "low",
      "latency": "low"
    },
    {
      "id": "reasoning-model",
      "description": "Strong reasoning, 200k context, and tool use",
      "cost": "high",
      "latency": "medium"
    }
  ],
  "priorities": [
    "quality",
    "context",
    "tool_use",
    "cost"
  ],
  "constraints": [
    "Customer data must remain within approved tools"
  ],
  "stakes": "high"
}

View the native request sent to OmniaKey

{
  "model": "jev-latest",
  "state": {
    "task": "Review a complex customer dispute with 100k context and tool use",
    "candidates": [
      {
        "id": "fast-model",
        "description": "Fast general model with 32k context",
        "cost": "low",
        "latency": "low"
      },
      {
        "id": "reasoning-model",
        "description": "Strong reasoning, 200k context, and tool use",
        "cost": "high",
        "latency": "medium"
      }
    ],
    "priorities": [
      "quality",
      "context",
      "tool_use",
      "cost"
    ],
    "constraints": [
      "Customer data must remain within approved tools"
    ],
    "stakes": "high"
  },
  "questions": {
    "model": {
      "type": "choice",
      "instructions": "Select the best approved candidate using the stated quality, context, tools, cost, latency, and stakes. Do not assume undocumented capabilities. Choose escalate when no candidate is adequate or evidence is insufficient.",
      "criteria": {
        "fast-model": "Choose this approved model if its documented capabilities satisfy the task, priorities, constraints, and stakes: {\"id\":\"fast-model\",\"description\":\"Fast general model with 32k context\",\"cost\":\"low\",\"latency\":\"low\"}",
        "reasoning-model": "Choose this approved model if its documented capabilities satisfy the task, priorities, constraints, and stakes: {\"id\":\"reasoning-model\",\"description\":\"Strong reasoning, 200k context, and tool use\",\"cost\":\"high\",\"latency\":\"medium\"}",
        "escalate": "No approved candidate can safely satisfy the task, or the provided evidence is insufficient to select one."
      }
    }
  }
}

Create an access key

Structured response

answers + probabilities + usage

The typed Jev response will appear here.

Run the request to inspect the original Jev answers, confidence, probability distributions, resolved model version, and token usage returned through OmniaKey.