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.
npx skills add https://github.com/Superior-Trade/superior-skills --skill donchian-strong-regime
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)from 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
{
"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.
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.
Use when implementing any feature or bugfix, before writing implementation code
Use when you have a spec or requirements for a multi-step task, before touching code
Use when creating new skills, editing existing skills, or verifying skills work before deployment
Use when writing or improving README files. Not all READMEs are the same — provides templates and guidance matched to your audience and project type.
| Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
Official Opentrons Protocol API for OT-2 and Flex robots. Use when writing protocols specifically for Opentrons hardware with full access to Protocol API v2 features. Best for production Opentrons protocols, official API compatibility. For multi-vendor automation or broader equipment control use pylabrobot.
Take superior-trade/donchian-strong-regime from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.