Endpoint · extractionPOSThubvibe-io.com /work/data/anomalies
Anomaly detection on a time series: score recent periods against history with BigQuery AI.DETECT_ANOMALIES (TimesFM).
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Anomaly detection on a time series: score recent periods against history with BigQuery AI.DETECT_ANOMALIES (TimesFM). Give one table and its latest periods are scored against its own history, or a history and a target table. Returns every checked row with bounds, anomaly flag and probability, plus the anomaly count. Input: history_table, target_table, timestamp_col, data_col; optional target_last, threshold, id_cols.Overview
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UNRATED
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$10.00 per call
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https://hubvibe-io.com/work/data/anomalies
MCP server on this host: io.github.Its-fortunatefolly/hubvibe
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first 13 days ago · last 10 hr ago
23 free handshakes
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x402 · MPP evm, stripe, tempo
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Base USDC, Solana, Tempo USDC.e
Listed on?
Base, Solana
Handshakescomputed 2 days ago
0.701 from 20 free handshakes over 30 days · UNRATED ?
| Component | Weight | Measured | Lower bound ? | Adds | Short ? | Uncertain ? | |
|---|---|---|---|---|---|---|---|
| livenesscosts the most it answered at all |
0.60 | 1.00 | 0.693 | 0.416 | 0 | −0.184 | |
| latency p95 it answered as fast as its class |
0.20 | 0.67 | 0.426 | 0.085 | −0.067 | −0.048 | |
| price stability the price stayed where it was listed |
0.20 | 1.00 | 1.000 | 0.200 | 0 | 0 | |
| Composite | 1.00 | 0.701 | gap to 1.000 = 0.299 · 0.067 short · 0.233 uncertain | 0.701 | −0.067 | −0.233 |
Not measured: correctness · nobody paid; honesty · nobody paid; schema conformance · no answer had a published shape to check
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npx teppi-check https://hubvibe-io.com/work/data/anomaliescurl -s https://api.teppi.xyz/v1/trust/cap_01M317X6W36SK2R1ZXYMDGD07T