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Get Started Free →Use when writing a trend-breakdown short gated by a triple-confirmed strong-bear regime on Superior Trade — anything described as donchian short, structural breakdown, regime-gated trend follower, EMA-separation + ADX + N-bar return confirmation. Validated +6.69%/100% win/0% DD on BTC over 162d; designed to fire only in confirmed bear regimes (zero trades in chop by design). Pairs with bollinger-reverter-4h for full-regime coverage.
.claude/skills/superior-trade-donchian-strong-regime/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | -20% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 1% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 0% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 106% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 17% | 0% |
Trend-breakdown short, gated by a triple-confirmed strong-bear regime. Stays out of chop entirely. Validated on BTC/USDC:USDC over 162 days (2025-11-20 → 2026-05-01).
Searchable under: trend follower, breakdown, regime-gated, donchian short, structural break.
| Window | Trades | Win rate | Profit | Max DD | |---|---|---|---|---| | Full period (162d) | 6 | 100% | +6.69% | 0% | | First-half / strong bear (82d) | 6 | 100% | +6.69% | 0% | | Second-half / chop (80d) | 0 | — | 0% | 0% |
The triple-confirmation gate produced zero trades in the rangy second half — exactly the behavior a regime gate should produce. Every fired trade in the first half captured the trailing stop for profit.
In a confirmed strong-bear regime (ema separation, ADX, recent momentum all aligned), a close below the 24-bar low (4 days of structure) reliably continues lower. The gate prevents the strategy from firing during sideways/rangy markets where the same signal mean-reverts.
EMA50 / EMA200 - 1 < -0.06 (≥6% separation = deep structural downtrend, not a fresh cross)ADX(14) > 25 (trend strength confirmed)close.pct_change(30) < -0.10 (last 30 bars = ~5 days, actual downside momentum)close < lowest_24_bar_low AND regime gate satisfiedclose > highest_6_bar_high (24h ceiling break — local reversal)RSI > 55 (sustained rebound)dsl-exit-engine skill)pythonfrom freqtrade.strategy import IStrategy import pandas as pd import talib.abstract as ta class DonchianStrongRegimeStrategy(IStrategy): INTERFACE_VERSION = 3 timeframe = "4h" can_short = True stoploss = -0.05 trailing_stop = True trailing_stop_positive = 0.02 trailing_stop_positive_offset = 0.03 trailing_only_offset_is_reached = True minimal_roi = {"0": 100.0} # disable ROI; trailing + signal exits only process_only_new_candles = True startup_candle_count = 220 use_exit_signal = True def populate_indicators(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame: dataframe["lowest_24"] = dataframe["low"].rolling(24).min().shift(1) dataframe["highest_6"] = dataframe["high"].rolling(6).max().shift(1) dataframe["ema50"] = ta.EMA(dataframe, timeperiod=50) dataframe["ema200"] = ta.EMA(dataframe, timeperiod=200) dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14) dataframe["adx"] = ta.ADX(dataframe, timeperiod=14) dataframe["ema_sep"] = ( (dataframe["ema50"] - dataframe["ema200"]) / dataframe["ema200"] ) dataframe["ret_30"] = dataframe["close"].pct_change(30) dataframe["regime_strong"] = ( (dataframe["ema_sep"] < -0.06) & (dataframe["adx"] > 25) & (dataframe["ret_30"] < -0.10) ) return dataframe def populate_entry_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame: cond = ( (dataframe["close"] < dataframe["lowest_24"]) & dataframe["regime_strong"] ) dataframe.loc[cond, "enter_short"] = 1 dataframe.loc[cond, "enter_tag"] = "donchian_strong_bear" return dataframe def populate_exit_trend(self, dataframe: pd.DataFrame, metadata: dict) -> pd.DataFrame: cond = ( (dataframe["close"] > dataframe["highest_6"]) | ((dataframe["rsi"] > 55) & (dataframe["rsi"].shift(1) > 55)) ) dataframe.loc[cond, "exit_short"] = 1 return dataframe
json{ "exchange": {"name": "hyperliquid", "pair_whitelist": ["BTC/USDC:USDC"]}, "stake_currency": "USDC", "stake_amount": 100, "dry_run_wallet": {"USDC": 150}, "timeframe": "4h", "max_open_trades": 1, "minimal_roi": {"0": 100.0}, "stoploss": -0.05, "trading_mode": "futures", "margin_mode": "isolated", "entry_pricing": {"price_side": "same", "price_last_balance": 0.0}, "exit_pricing": {"price_side": "same", "price_last_balance": 0.0}, "pairlists": [{"method": "StaticPairList"}] }
This strategy only fires during confirmed strong-bear regimes. In bull markets, sideways markets, and weak bears it will trade rarely or not at all — by design. Do not "improve" by loosening the gate; the loose-gate version (without triple confirmation) lost money in the same window.
The 100% backtest win rate is partly a function of sample size (6 trades). The honest expectation is ~60-75% win rate with similar expectancy when the gate is properly confirmed across longer windows.
Pair this strategy with bollinger-reverter-4h (the chop-regime sibling) for full-spectrum coverage — they fire on mutually exclusive regimes.
| Parameter | Range | Effect | |---|---|---| | Regime EMA separation | -0.04 to -0.08 | Looser = more trades, more chop noise; tighter = fewer, cleaner | | Regime ADX threshold | 20 - 30 | Higher = more selective trend confirmation | | Regime return lookback | 20 - 40 bars | Window for "actual momentum" check | | Donchian lookback (low) | 18 - 36 | Length of structural floor | | Exit lookback (high) | 4 - 8 | Tighter exit = faster wins, more giveback | | Trail activate | 0.02 - 0.04 | Where Phase 2 kicks in | | Trail offset | 0.015 - 0.025 | Tightness once activated |
bollinger-reverter-4h skill (the chop-regime sibling)regime-overlay skilldsl-exit-engine skillRun as its own sub-account so the regime gate's "trade nothing for weeks" behavior doesn't fight a mean-reversion strategy in the same wallet. See your Superior Trade account setup for sub-accounts.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-04 | pass→pass | 17,041 | 15,368 | -10% | 1 | 1 | 0% | 3,096 | 4,732 | +53% | 0 | 0 | — |
case-01 | fail→pass | 54,130 | 29,790 | -45% | 1 | 1 | 0% | 8,274 | 6,651 | -20% | 0 | 0 | — |
case-02 | fail→pass | 37,667 | 18,465 | -51% | 1 | 1 | 0% | 6,153 | 6,187 | +1% | 0 | 0 | — |
case-03 | fail→pass | 33,104 | 18,719 | -43% | 1 | 1 | 0% | 5,172 | 5,190 | +0% | 0 | 0 | — |
case-05 | pass→pass | 19,046 | 21,538 | +13% | 1 | 1 | 0% | 3,475 | 6,334 | +82% | 0 | 0 | — |
case-06 | pass→pass | 23,604 | 30,063 | +27% | 1 | 1 | 0% | 3,340 | 6,940 | +108% | 0 | 0 | — |
case-07 | fail→pass | 13,370 | 19,177 | +43% | 1 | 1 | 0% | 2,340 | 4,815 | +106% | 0 | 0 | — |
case-08 | pass→pass | 17,469 | 13,147 | -25% | 1 | 1 | 0% | 2,566 | 4,024 | +57% | 0 | 0 | — |
case-21 | pass→pass | 7,305 | 5,319 | -27% | 1 | 1 | 0% | 1,072 | 2,799 | +161% | 0 | 0 | — |
case-09 | fail→pass | 21,608 | 8,980 | -58% | 1 | 1 | 0% | 2,894 | 3,382 | +17% | 0 | 0 | — |
case-10 | fail→pass | 23,066 | 16,634 | -28% | 1 | 1 | 0% | 4,236 | 4,626 | +9% | 0 | 0 | — |
case-11 | fail→pass | 23,475 | 13,748 | -41% | 1 | 1 | 0% | 3,124 | 4,351 | +39% | 0 | 0 | — |
case-12 | pass→pass | 18,831 | 14,750 | -22% | 1 | 1 | 0% | 2,884 | 4,448 | +54% | 0 | 0 | — |
case-13 | pass→pass | 19,220 | 12,608 | -34% | 1 | 1 | 0% | 2,774 | 3,752 | +35% | 0 | 0 | — |
case-14 | pass→pass | 15,597 | 20,671 | +33% | 1 | 1 | 0% | 2,718 | 5,180 | +91% | 0 | 0 | — |
case-15 | fail→pass | 13,871 | 11,555 | -17% | 1 | 1 | 0% | 1,923 | 3,994 | +108% | 0 | 0 | — |
case-16 | fail→pass | 13,464 | 3,601 | -73% | 1 | 1 | 0% | 2,163 | 2,519 | +16% | 0 | 0 | — |
case-17 | fail→pass | 12,545 | 10,452 | -17% | 1 | 1 | 0% | 2,174 | 3,388 | +56% | 0 | 0 | — |
case-18 | pass→pass | 12,342 | 7,862 | -36% | 1 | 1 | 0% | 1,685 | 3,178 | +89% | 0 | 0 | — |
case-19 | fail→pass | 15,356 | 6,680 | -56% | 1 | 1 | 0% | 2,481 | 2,999 | +21% | 0 | 0 | — |
case-20 | fail→pass | 14,851 | 4,159 | -72% | 1 | 1 | 0% | 2,473 | 2,807 | +14% | 0 | 0 | — |
case-22 | pass→pass | 5,022 | 4,501 | -10% | 1 | 1 | 0% | 556 | 2,554 | +359% | 0 | 0 | — |
case-23 | fail→pass | 83,356 | 3,351 | -96% | 1 | 1 | 0% | 1,754 | 2,481 | +41% | 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 +57 percentage points is the difference between those two pass rates over the 23 comparable cases.
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.
Other measured skills in the registry, with their headline benchmark lift.