VIGIL Trust Score for the AI Agent Economy
Trader 0x726239...
0x7262396eecb0ad4cb7511545c15fb0605a5ae728
Polymarket Trader
DANGER
High probability of further losses.
Calibration Analysis
When this trader buys at $0.70, they imply 70% probability. Perfect calibration = the event happens 70% of the time.
| Bucket | Bets | Expected | Actual | Error |
|---|
| 0.00-0.10 | 2 | 2% | 0% | 2.4% |
| 0.90-1.00 | 1 | 99% | 100% | 1.0% |
Calibration Error: 1.9%
Reliability (CAL)
0.0004
Lower = better calibrated
Resolution (RES)
0.2222
Higher = stronger opinions
Brier Skill Score
99.8%
vs naive baseline
Log Loss
0.0192
Skill: 97.0% vs naive — sensitive to rare events
Skill & Variance Analysis
Skill measures calibration quality (0-100). Variance measures return volatility (0-100, higher = more volatile).
Signals
✓ Well-diversified: 28 unique markets
✓ On-chain: multi-protocol user (USDC, USDC.e (Bridged), Polymarket Neg Risk Adapter)
⚠ Limited resolved data (3 resolved) despite 105 trades across 28 markets — older positions may have been purged from API
⚠ On-chain: wallet only 0 days old on Polygon
⚠ On-chain: bot-like trading patterns detected (bot score: 60)
On-Chain Verification (Polygon)
Protocols: USDC, USDC.e (Bridged), Polymarket Neg Risk Adapter
PnL verified: $1.08 gap between API and on-chain USDC
⚠ Very new wallet: 0 days old — possible sybil
⚠ Bot-like behavior detected: 5 burst txs, median interval 20s
Reasoning
On-chain verification: wallet age 0 days, 151 txs, provenance grade D. Bot score: 60/100, wash trading score: 20/100.
105 total trades across 28 markets.
3 bets on resolved markets available for calibration scoring.
Insufficient resolved bets for calibration analysis.
Skill: 93/100 (calibration quality). Variance: 23/100 (higher = more volatile returns).
What Does F/28 Mean?
No demonstrated forecasting skill. This trader performs at or below random chance based on available data.
Confidence: F/28 ± 25 (very_low confidence, 3 resolved bets). Low confidence — take this score with a grain of salt until more markets resolve.
Methodology: Brier Score Decomposition (Murphy 1973), Log Loss, On-Chain USDC Verification. Same approach used by IARPA to identify superforecasters.