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Get Started Free →Use when two Polymarket markets imply different probabilities for a linked outcome.
.claude/skills/superior-trade-related-market-spread/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 0% | 0% |
| case-03 | ✗→✓ | ▲ Improved | -19% | 0% |
| case-18 | ✗→✓ | ▲ Improved | -7% | 0% |
| case-08 | ✗→✓ | ▲ Improved | -48% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 24% | 0% |
Use this when the user asks for relative-value trades, discrepancy checks, linked outcomes, or questions like "this market is mispriced versus that one."
POST /v3/markets/search.Partial fit. Backtests built from filled TradeTick data are useful for checking whether the spread relationship has widened and then compressed in history. They cannot guarantee simultaneous fills or full cross-book liquidity.
Use this as a generated archetype: the strategy should be adapted in code before use, not treated as a finished edge.
Track the latest filled price for both legs. Enter when spread is above a threshold and exits when spread narrows or max holding duration expires.
TradeTick for both instruments.json{ "primary_instrument_id": "AUTO_FROM_MARKET_A", "secondary_instrument_id": "AUTO_FROM_MARKET_B", "spread_entry": 0.08, "spread_exit": 0.03, "order_size": 10, "max_holding_ticks": 120 }
| Knob | Effect | |---|---| | spread_entry | Higher = only trade stronger relative-value discrepancies. | | spread_exit | Lower = wait for fuller normalization before exiting. | | max_holding_ticks | Lower = tighter time risk control if convergence does not happen. |
TradeTick replay cannot prove simultaneous execution across legs."This is a relative-value archetype, not a guaranteed edge. It is built from filled TradeTick backtests and exact market slug discovery first, then adapted into custom NautilusTrader code before any deployment."
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→pass | 29,003 | 21,857 | -25% | 1 | 1 | 0% | 4,679 | 4,701 | +0% | 0 | 0 | — |
case-02 | fail→fail | 27,916 | 20,748 | -26% | 1 | 1 | 0% | 4,073 | 4,054 | -0% | 0 | 0 | — |
case-03 | fail→pass | 30,885 | 21,862 | -29% | 1 | 1 | 0% | 6,215 | 5,018 | -19% | 0 | 0 | — |
case-04 | pass→pass | 20,099 | 19,456 | -3% | 1 | 1 | 0% | 3,989 | 4,791 | +20% | 0 | 0 | — |
case-05 | pass→pass | 27,238 | 23,420 | -14% | 1 | 1 | 0% | 4,592 | 4,958 | +8% | 0 | 0 | — |
case-06 | pass→fail | 30,062 | 18,983 | -37% | 1 | 1 | 0% | 4,220 | 3,940 | -7% | 0 | 0 | — |
case-07 | pass→pass | 25,836 | 32,751 | +27% | 1 | 1 | 0% | 4,215 | 7,107 | +69% | 0 | 0 | — |
case-18 | fail→pass | 31,207 | 18,532 | -41% | 1 | 1 | 0% | 4,687 | 4,379 | -7% | 0 | 0 | — |
case-08 | fail→pass | 13,185 | 3,387 | -74% | 1 | 1 | 0% | 2,012 | 1,050 | -48% | 0 | 0 | — |
case-09 | fail→pass | 17,088 | 16,834 | -1% | 1 | 1 | 0% | 2,464 | 3,050 | +24% | 0 | 0 | — |
case-10 | pass→pass | 16,388 | 12,310 | -25% | 1 | 1 | 0% | 2,251 | 2,658 | +18% | 0 | 0 | — |
case-11 | fail→pass | 22,047 | 10,383 | -53% | 1 | 1 | 0% | 3,572 | 2,204 | -38% | 0 | 0 | — |
case-12 | pass→pass | 14,843 | 9,646 | -35% | 1 | 1 | 0% | 1,959 | 1,906 | -3% | 0 | 0 | — |
case-19 | fail→pass | 21,987 | 11,877 | -46% | 1 | 1 | 0% | 3,167 | 2,177 | -31% | 0 | 0 | — |
case-13 | pass→pass | 19,555 | 9,964 | -49% | 1 | 1 | 0% | 3,124 | 1,782 | -43% | 0 | 0 | — |
case-14 | pass→pass | 10,185 | 7,157 | -30% | 1 | 1 | 0% | 1,517 | 1,664 | +10% | 0 | 0 | — |
case-15 | pass→pass | 16,838 | 16,001 | -5% | 1 | 1 | 0% | 2,562 | 2,835 | +11% | 0 | 0 | — |
case-16 | pass→pass | 17,968 | 13,904 | -23% | 1 | 1 | 0% | 2,398 | 2,601 | +8% | 0 | 0 | — |
case-17 | pass→pass | 15,886 | 13,224 | -17% | 1 | 1 | 0% | 2,689 | 3,006 | +12% | 0 | 0 | — |
case-20 | fail→pass | 14,871 | 3,559 | -76% | 1 | 1 | 0% | 2,160 | 1,155 | -47% | 0 | 0 | — |
case-21 | pass→pass | 14,942 | 6,194 | -59% | 1 | 1 | 0% | 2,075 | 1,611 | -22% | 0 | 0 | — |
case-22 | fail→pass | 12,517 | 4,247 | -66% | 1 | 1 | 0% | 1,771 | 1,208 | -32% | 0 | 0 | — |
case-23 | pass→pass | 11,050 | 3,162 | -71% | 1 | 1 | 0% | 1,619 | 1,159 | -28% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +35 percentage points is the difference between those two pass rates over the 23 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
| Model | Method | Date | Lift |
|---|---|---|---|
| gemini-3.6-flash | verified | 8/28/2026 | +32% |
Other measured skills in the registry, with their headline benchmark lift.