Install
openclaw skills install crypto-trading-decision-frameworkStructured decision system for crypto traders — position sizing, entry checklist, exit framework, and halt decision tree. Eliminates ad-hoc calls and enforces disciplined risk management on every trade. Use when sizing a new position, evaluating an entry, managing a live trade, or deciding when to halt a strategy. Prevents the most common trader failure modes: oversizing, moving stops, and holding losers.
openclaw skills install crypto-trading-decision-frameworkBottom line: Every trade decision runs through 3 gates — sizing, entry checklist, exit plan. If any gate fails, the trade doesn't happen. No exceptions.
Any trading discussion that involves:
Position size (notional) = (Risk % ÷ Stop distance %) × Liquid portfolio
Example: 1% risk, 1.5% stop distance → (1/1.5) × $50,000 = ~$33,333 notional
For leveraged accounts: cap leverage at 3× for new strategies, 5× for proven strategies with n≥50 live trades.
Scoring:
| Strategy type | Minimum R:R | Win rate floor |
|---|---|---|
| Mean reversion | 1.5:1 | 60% |
| Trend following | 2.5:1 | 40% |
| Breakout | 3:1 | 35% |
| News-driven / event | 4:1 | 30% |
| Funding/yield carry | N/A | N/A |
If a setup doesn't clear BOTH the R:R minimum and the historical win rate floor → DO NOT RECOMMEND.
When a live strategy is underperforming, work through this tree top to bottom:
1. Has the strategy hit its account-level kill-switch loss?
YES → HALT immediately. Post-mortem before any restart.
NO → next step.
2. Has the strategy hit -3R drawdown beyond its expected backtest MDD?
YES → PAUSE for 5 trading days. Re-evaluate regime fit.
NO → next step.
3. Is the live profit factor ≤ 50% of backtest PF over n≥10 live trades?
YES → SHRINK position size 50%, run another 10 trades, re-evaluate.
NO → next step.
4. Has the strategy produced zero signals for N days, where N > 2× expected signal frequency?
YES → Strategy is dead in current regime. KILL or re-tune thresholds.
NO → Normal volatility. No action needed.
These always require human approval — never autonomous execution:
For any deployment of significant capital:
If 2+ models disagree → defer 24h, re-run consensus tomorrow. Disagreement = edge case, not clear enough to act.
Always attach 3 tags to any trade call:
Example: "Confidence 82% / Research Depth 75% / Reality Gap 20%"
This keeps recommendations honest and prevents overconfidence drift.
When this framework produces a trade recommendation, structure it as:
## Trade Recommendation: [ASSET] [LONG/SHORT]
**Thesis:** [1-2 sentences — why this setup exists]
**Regime fit:** [why current market supports this strategy type]
**Sizing:**
- Portfolio size: $X
- Risk per trade: $X (1%)
- Stop distance: X%
- Position notional: $X
**Entry checklist:** X/10 YES [list any NO items]
**R:R:** X:1 [minimum met: YES/NO]
**Levels:**
- Entry: $X
- Hard stop: $X (thesis invalidated if price reaches here because: [reason])
- TP1: $X (partial exit X%)
- TP2: $X (partial exit X%)
- Time stop: [date/bar count]
**Confidence:** X% / Research Depth X% / Reality Gap X%
**Escalation required:** YES/NO [why]