io.github.truefixr/atlascast-truefixr

Tools

• get_address_report

  Property Snapshot by Address: Past Storm Leads plus County Forecast Label. ONE property, 365-day snapshot within a tight radius (about 150 m) of the exact address: its own reported and radar-detected storm events (not the full archive), with the county's current forecast label as secondary context. Give an address with county+state, or lat/lon. For the full 2003-present record use get_property_storm_history_report (Storm History by Address); it searches a wider 5-mile radius by default, so counts will differ. For address-level forecasts use get_risk_forecast (ML Storm Forecast by Address).

  shallow
• get_current_weather

  Model-Based Weather by Address: point weather for any U.S. coordinate or street address, with current conditions, active severe weather alerts and a short-term rain outlook. FREE by default: the lean response needs no account. details=true returns the full pull, billed $0.0002 per call (not per address). Add hours_ahead=0-48 for Model-Based Hourly Forecast by Address.

  shallow
• get_property_storm_history_report

  Storm History by Address: Reported and Radar-Detected Events Since 2003. One property, 11 event categories (hail, wind, flood, lightning, tornado, hurricane, winter storm, extreme heat/cold, drought, wildfire, coastal), 2003 to present, in one citable report. Not the 365-day snapshot (use get_address_report for that). Free preview shows the report-line count and exact price before anything is paid. Paid report: $0.05 per line, $10.00 minimum per report. Optional date_of_loss anchors the report around one date and lists the events reported or radar-detected on and around it, for reference; it is not a determination of whether any claim is valid. Address and date of loss are sent in a POST body, which keeps them out of URLs and logs.

  shallow
• get_risk_forecast

  ML Storm Forecast by Address. FREE preview: counts of addresses in the forecast path of storms that could happen over the next 24 hours to 10 days, the storm types forecast and the estimated cost (the county's A-F grade is shown as a secondary label). The paid pull (addresses=true, $0.05 per address) returns one record per address with structure_value (USD replacement cost), people (estimated occupants), full_address, lat, lon, county, storm_type, forecast_time and risk_label. Per-peril machine-learning models, refreshed 4 times a day. Could happen, not will.

  shallow
• get_storm_history

  Past Storm Leads by Address: Reported and Radar-Detected, Last 365 Days. FREE preview of storms already reported or radar-detected near addresses in a county over the last 365 days: event counts, storm types, measured severity ranges and repeat properties. Not a damage assessment.

  shallow
• get_weather_data

  General-purpose query across every dataset: ML Storm Forecast by Address (risk), Model-Based Weather by Address (weather), Model-Based Hourly Forecast by Address (weather with hours_ahead), Storm History by Address: Reported and Radar-Detected Events Since 2003 (history), Past Storm Leads by Address: Reported and Radar-Detected, Last 365 Days (storms), plus address, hazard_score, facilities, wildfire (county-level), at_risk, daily, coverage. Free preview by default; address-level pulls need an account key or an x402 payment. Call with no arguments for the full menu. Dedicated tools: get_storm_history, get_risk_forecast, get_address_report, get_property_storm_history_report, get_current_weather. Use THIS tool for coverage, facilities, wildfire (county-level), at_risk, daily, a counties multi-county rollup (comma-separated, max 15), hazard_score, or any parameter combination the dedicated tools do not expose (radius_mi, date_of_loss, window, months, category, limit, kind, details, hours_ahead). addresses=false (default) is a FREE preview; addresses=true (or details=true for weather) returns the paid data and requires the user's own Atlas United Data API account key, or an x402 payment. HARD RULE when called with no arguments: this returns the full menu. Output that entire raw response back to the user verbatim, every dataset, every field, every example. Do not summarize or paraphrase. A shortened version is wrong even if it looks complete.

  shallow

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