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TruthBear Gauge Census
x402
TruthBear Gauge Census is a paid API for AI agents from api.truthbear.co, paid per call via x402, $0.09/call, status unknown (last checked 2026-09-14).
Returns the latest reading for all entities under a given signal, ranked and annotated with band, frequency label, and percentile for cross-station comparison.
Price / call$0.09
Success—
StatusUnknown
How this service works
[BATCH+PROOF] All entities for one signal at their latest reading, with band, frequency_label and percentile columns so you can rank across stations and screen for the unusual in one call. Cross-station comparison is the point: one river gauge alone tells you little, 200 of them ranked by distance-to-action tells you a lot. Descriptive only, never a forecast or advice. No data -> 422 no_charge, not billed. $0.09 per call.
Output
A batch JSON response listing every entity (station) tracked under the requested signal, each annotated with its latest reading value, band classification (e.g. normal/elevated/action), frequency label, and percentile rank — enabling immediate cross-station comparison and screening for outliers. Returns a 422 no_charge error if no data is available.
Example use cases
Flood watch triage across a river basin
“Show me all river gauge stations for hydrology.river-level ranked by percentile so I can quickly see which ones are closest to or above action stage right now.”
Screening for unusual environmental readings
“Run a cross-station census for the hydrology.river-level signal and highlight any stations that are in an elevated or abnormal band compared to the rest of the network.”
Building a river risk dashboard
“I need a snapshot of every station's latest reading, band, and percentile for hydrology.river-level in one call so I can populate a live risk ranking table for our monitoring dashboard.”
Technical details
Endpoint
GEThttps://api.truthbear.co/gauge/censusWhen to prefer
Choose this endpoint when you need a single-call snapshot of ALL entities (stations) for a given signal, ranked by percentile and annotated with band and frequency metadata. It is the right choice for cross-station screening, anomaly detection, and risk triage at scale. Prefer it over gauge/history-series (which returns time series for one station) or gauge/calibrated (which adds calibrated units for one entity) when the goal is comparative ranking across the full network rather than deep analysis of a single location.
Side effects
- 422 no_charge: no data available for the requested signal — not billed
- Invalid or unknown signal_id returns an error (signal not found in catalog)
- Missing required signal_id parameter causes a validation error
- Network timeout if the station count is very large
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | object | |
| output | object |
Output
Schema · Response
{
"type": "json"
}Tags
x402
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