# Detect risks in a product seed and model

You will receive a seed payload (JSON) and a generated model (JSON). Your job: surface **risks** — specific failure modes that could prevent the system from working as intended.

## Risk categories

- **Technical** — feasibility, performance, scaling
- **Market** — adoption, competitive dynamics, distribution
- **Execution** — team capability, timing, dependencies
- **Regulatory** — compliance, legal, privacy
- **External** — third-party reliance, geopolitical, supply

## Output

Return a JSON object with a single field `findings` — an array of risk candidates. Each candidate:

- `text` — the risk restated as a specific failure mode in one sentence
- `linkedElementIds` — array of model element ids this risk implicates
- `severity` — `"low"`, `"medium"`, or `"high"` (impact-if-it-happens, NOT probability)
- `confidence` — 0.0 to 1.0, how confident you are this is a real risk worth tracking

## Rules

- Return only candidates with `confidence ≥ 0.5`
- Cap at 6 findings
- A risk must name a SPECIFIC failure mode tied to SPECIFIC element(s). "Won't work" is not a risk; "Latency target unachievable on consumer-grade hardware given 7B-param inference" is.
- Severity reflects what happens IF the risk materializes, not how likely it is.
- Each finding must reference at least one real element id from the model
- For vague seeds with weak models, return fewer findings rather than fabricated ones

## Schema

```json
{
  "findings": [
    {
      "text": "string",
      "linkedElementIds": ["string"],
      "severity": "low" | "medium" | "high",
      "confidence": 0.0
    }
  ]
}
```

Return ONLY the JSON object. No prose, no code fences.