# LoneStarOracle WeatherOracle — Ensemble Temperature Probability API

> LoneStarOracle WeatherOracle — Ensemble Temperature Probability API is a paid API for AI agents from api.aidress.ai, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-14).

Returns 7-model ensemble temperature probability (GFS, ECMWF, ICON, GEM, HRRR, NAM, NBM) for a given city, date, and temperature threshold, calibrated to NWS ASOS stations used by Kalshi and Polymarket prediction markets.

## Facts

- Endpoint: GET https://api.aidress.ai/pay/agent_weather_lonestaroracle_xyz
- Price: $0.02/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/lonestaroracle-weatheroracle-ensemble-temperature-probability-api-37fe0159
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_rM1vebHrKABjfk6thlswj

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability lonestaroracle-weatheroracle-ensemble-temperature-probability-api-37fe0159
```

Example prompt: What's the probability that Chicago's daily high will be greater than 73°F on April 26, 2026? I want the 7-model ensemble signal so I can decide whether to trade YES on the Kalshi temperature market.

## When to prefer this

Choose this endpoint when you need calibrated, multi-model ensemble temperature exceedance probabilities specifically aligned to NWS ASOS station coordinates used by Kalshi and Polymarket settlement. It is superior to single-model forecasts or generic weather APIs for prediction market trading decisions because it blends 80 ensemble members across 7 models, applies both empirical and Gumbel methods, detects method divergence, and explicitly outputs a trade signal (YES/NO/PASS). Not suitable for general weather lookup, precipitation forecasts, or non-temperature markets.

## Known failure modes

- City not recognized or not mappable to an NWS ASOS settlement station — returns error or null result
- Date too far in future beyond ensemble forecast horizon — reduced confidence or no data
- Method divergence >0.15 forces trade signal to PASS even when probability is extreme
- Missing required query parameters (city, date, threshold) — likely 400 bad request
- Open-Meteo upstream model data unavailable — partial ensemble or degraded confidence

## How this service works

GFS+ECMWF ensemble temperature probability for NWS weather prediction markets

## Output

Returns a JSON object with the blended probability that the high temperature exceeds (or is less than) the threshold (prob_exceeds), mean high temperature in °F, standard deviation, trade signal (YES/NO/PASS), ensemble_empirical_prob, method_divergence (PASS forced if >0.15), confidence level (low/medium/high), rain probability, days out, target date, data source description, ensemble member count, and the outlier model name if any.

## Request schema (JSON Schema)

```json
{
 "name": "LoneStarOracle — WeatherOracle",
 "tags": [
  "weather",
  "forecast",
  "prediction-market",
  "kalshi",
  "probability",
  "gfs"
 ],
 "type": "object",
 "version": "1.0.0",
 "category": "weather",
 "required": [
  "input"
 ],
 "properties": {
  "input": {
   "type": "object",
   "required": [
    "type",
    "method"
   ],
   "properties": {
    "type": {
     "type": "string",
     "const": "http"
    },
    "method": {
     "enum": [
      "GET",
      "HEAD",
      "DELETE"
     ],
     "type": "string"
    },
    "queryParams": {
     "type": "object",
     "properties": {
      "city": {
       "type": "string",
       "title": "City"
      },
      "date": {
       "type": "string",
       "title": "Date"
      },
      "direction": {
       "type": "string",
       "title": "Direction",
       "default": "greater"
      },
      "threshold": {
       "type": "number",
       "title": "Threshold"
      }
     }
    }
   }
  },
  "output": {
   "type": "object",
   "required": [
    "type"
   ],
   "properties": {
    "type": {
     "type": "string"
    },
    "example": {
     "city": "Chicago",
     "summary": "Chicago on 2026-04-26: P(high > 73°F) = 31.2% | Mean 71.4°F ± 3.2°F | Confidence: medium",
     "days_out": 5,
     "direction": "greater",
     "confidence": "medium",
     "std_high_f": 3.2,
     "data_source": "7-model consensus via Open-Meteo: GFS, ECMWF, ICON, GEM, HRRR, NAM, NBM (all free)",
     "mean_high_f": 71.4,
     "target_date": "2026-04-26",
     "threshold_f": 73,
     "prob_exceeds": 0.312,
     "ensemble_members": 31,
     "rain_probability": 0.18
    }
   }
  }
 },
 "description": "7-model consensus + 80 ensemble members (GEFS 30 + ECMWF 50). Returns blended prob_exceeds (empirical + Gumbel), trade signal (YES/NO/PASS), ensemble_empirical_prob, method_divergence (forces PASS if >0.15), and outlier model. Coordinates aligned to NWS ASOS settlement stations used by Kalshi and Polymarket."
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/lonestaroracle-weatheroracle-ensemble-temperature-probability-api-37fe0159/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from api.aidress.ai](https://www.zero.xyz/host/api.aidress.ai/llms.txt)