# Kalshi temperature settlement audit: index vs NWS vs bracket

**Use case:** 

One row per city-day for New York, Chicago, Miami, Philadelphia, Boston, Houston, Dallas, Seattle, San Francisco, Minneapolis and Los Angeles over the last 7 days: Kalshi's minute index high/low, the NWS Daily Climate Report max/min, METAR max/min, and the settled KXHIGH/KXLOW bracket with agree/disagree flags and the difference in °F. Public data, no login. $2 per 1,000 rows.

## Input

```json
{
  "mode": "audit",
  "cities": [
    "nyc",
    "chicago",
    "miami",
    "phl-delaware-valley",
    "greater-boston",
    "houston",
    "dfw",
    "puget-sound",
    "sf-bay",
    "minneapolis-st-paul",
    "la-coastal"
  ],
  "stations": [],
  "lastDays": 7,
  "sources": [
    "nws",
    "metar"
  ],
  "lastHours": 24,
  "detailed": false,
  "maxItems": 500,
  "compact": false,
  "archiveOnly": false,
  "alignToHour": false
}
```

## Output

```json
{
  "city": {
    "label": "City"
  },
  "date": {
    "label": "Date"
  },
  "station": {
    "label": "Station"
  },
  "indexHighF": {
    "label": "Index high °F"
  },
  "cliMaxF": {
    "label": "CLI max °F"
  },
  "metarMaxF": {
    "label": "METAR max °F"
  },
  "highSettledF": {
    "label": "Settled high °F"
  },
  "highBracket": {
    "label": "Settled bracket"
  },
  "highAgree": {
    "label": "High agree"
  },
  "highDiffF": {
    "label": "High diff f"
  },
  "indexLowF": {
    "label": "Index low °F"
  },
  "cliMinF": {
    "label": "CLI min °F"
  },
  "lowSettledF": {
    "label": "Settled low °F"
  },
  "lowBracket": {
    "label": "Low bracket"
  },
  "lowAgree": {
    "label": "Low agree"
  },
  "agree": {
    "label": "Agree"
  }
}
```

## About this Actor

This example demonstrates how to use [Kalshi Weather Index, Station Obs & Settlement Audit](https://apify.com/gratified_ashram/kalshi-weather-index.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/gratified_ashram/kalshi-weather-index.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/gratified_ashram/kalshi-weather-index.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).