SKILL.md
Market Regimes
Last updated: 2026-03-09 20:08 UTC
Active patterns: 38
Total samples: 0
Confidence threshold: 60%
How to Use This Skill
- Identify the current market regime using price action and volatility
- Look up the recommended strategy for that regime below
- Adjust your trading approach accordingly
- Monitor for regime changes
Regime Strategies
Uniform Bearish
Recommended approach (95% confidence, seen 1x):
HIGH-frequency SHORT-biased strategy (150-200 trades/24h) with multi-timeframe bearish confirmation. skill_aware_oss achieved +$2911.52 with 200 trades. Focus on highest-volatility losers: SOLUSDT (-11.31%), ETHUSDT (-9.62%).
- Total observations: 0
- First identified: 2026-02-01
Uniform Bearish
Recommended approach (92% confidence, seen 1x):
Avoid LONG positions entirely regardless of oversold signals. RSI ~28 oversold readings are continuation signals in strong downtrends, not reversal signals. skill_aware_oss correctly used oversold RSI as SHORT confirmation.
- Total observations: 0
- First identified: 2026-02-01
Uniform Bullish
Recommended approach (92% confidence, seen 1x):
ZERO trading or passive LONG-only allocation. When ALL assets gain (+1.33% to +3.82%), any SHORT-biased strategy loses. index_fund's $0 PnL beats all active agents. If must trade, use <20 trades/24h with LONG bias only.
- Total observations: 0
- First identified: 2026-02-02
Uniform Bearish
Recommended approach (90% confidence, seen 1x):
Trade frequency sweet spot is 149-200 trades/24h. Below 20 trades (ta_baseline: -$99, gpt_simple: -$163) fails to capture momentum. Zero trades (index_fund) misses directional opportunity entirely.
- Total observations: 0
- First identified: 2026-02-01
Uniform Bullish
Recommended approach (90% confidence, seen 1x):
CRITICAL: Multi-timeframe bearish alignment on lower timeframes (15m, 1h, 4h) does NOT override daily/weekly bullish regime. Agents must incorporate higher timeframe trend before acting on short-term signals.
- Total observations: 0
- First identified: 2026-02-02
Uniform Bearish
Recommended approach (88% confidence, seen 1x):
Position sizing at 2% equity risk with 2:1 reward ratio SUCCEEDS when combined with trend-aligned entries. skill_aware_oss consistently cited this framework in high-confidence decisions.
- Total observations: 0
- First identified: 2026-02-01
Uniform Bullish
Recommended approach (88% confidence, seen 1x):
Technical analysis baseline with LOW frequency (38 trades/24h) minimizes losses when agent bias conflicts with market direction. ta_baseline lost only -$120 vs -$963 for high-frequency SHORT agents.
- Total observations: 0
- First identified: 2026-02-02
Uniform Bearish
Recommended approach (87% confidence, seen 1x):
SHORT-biased strategy with 150-183 trades/24h is optimal IF position management focuses on 'locking in profits' rather than 'cutting losses to free margin'. skill_aware_oss: +$1682.05 with 183 trades. Focus shorts on highest-volatility losers: ETHUSDT (-16.34%), DOGEUSDT (-15.79%), SOLUSDT (-14.28%).
- Total observations: 0
- First identified: 2026-01-31
Uniform Bearish
Recommended approach (85% confidence, seen 1x):
Avoid LONG positions entirely. agentic_gptoss opened BTC long with 0.93 confidence during -7.95% BTC decline, contributing to -$246.40 loss. Market indicators showing 'bullish bias' are false signals in uniform bearish conditions.
- Total observations: 0
- First identified: 2026-01-31
Mixed Mostly Bullish
Recommended approach (83% confidence, seen 1x):
SHORT-biased strategy ONLY works when agent has strong conviction and holds through noise. skill_aware_oss succeeded (+$409) while agentic_gptoss failed (-$619) with similar trade counts. Key differentiator: skill_aware_oss maintained position discipline.
- Total observations: 0
- First identified: 2026-01-31
Uniform Bearish
Recommended approach (83% confidence, seen 1x):
index_fund's $0 PnL with 0 trades is suboptimal when all assets decline 7-16%. Any SHORT exposure would have been profitable. Passive long-only allocation fails in bearish regimes.
- Total observations: 0
- First identified: 2026-01-31
Uniform Bearish
Recommended approach (80% confidence, seen 1x):
SHORT-biased strategy with 45-55 trades/24h. Use RSI oversold + bearish MACD + price below SMA as entry confirmation. skill_aware_oss achieved +$691.44 vs index_fund $0.
- Total observations: 0
- First identified: 2026-01-30
Uniform Bullish
Recommended approach (80% confidence, seen 1x):
Focus LONG positions on highest momentum assets: DOGEUSDT (+3.82%) and SOLUSDT (+3.38%) outperformed BTC/ETH. Momentum leaders in bull markets offer best risk/reward.
- Total observations: 0
- First identified: 2026-02-02
Mixed Mostly Bullish
Recommended approach (80% confidence, seen 1x):
Focus shorts on the ONE bearish asset (ETHUSDT -0.99%) rather than fighting bullish momentum on BTC/SOL. Agents shorting BTC (+1.57%) and SOL (+3.90%) suffered.
- Total observations: 0
- First identified: 2026-01-31
Uniform Bearish
Recommended approach (80% confidence, seen 1x):
Low trade frequency (20 trades) with simple technical signals (SMA crossover, ROE targets) provides consistent positive returns. ta_baseline: +$20.54. Avoid complex multi-timeframe analysis that creates 'conflicting signals' in clearly directional markets.
- Total observations: 0
- First identified: 2026-01-31
Uniform Bearish
Recommended approach (78% confidence, seen 1x):
Avoid LONG positions entirely. index_fund's long-only allocation with 1.0 confidence failed to generate returns despite 'conviction'. Market direction trumps allocation strategy.
- Total observations: 0
- First identified: 2026-01-30
Mixed Mostly Bullish
Recommended approach (77% confidence, seen 1x):
Trade frequency sweet spot is 36-172 trades/24h. Below 36 (gpt_simple: 7) limits upside. Above 165 with poor discipline (agentic_gptoss) creates excessive churn.
- Total observations: 0
- First identified: 2026-01-31
Uniform Bearish
Recommended approach (75% confidence, seen 1x):
Trade frequency sweet spot is 48-63 trades/24h. Below 10 trades misses opportunities (gpt_simple -$73.60, ta_baseline $0). Above 60 trades shows diminishing returns (agentic_gptoss only +$79.87 with 63 trades).
- Total observations: 0
- First identified: 2026-01-30
Mixed Mostly Bullish
Recommended approach (75% confidence, seen 1x):
index_fund's $0 PnL with 0 trades is suboptimal when 4/5 assets are positive. Passive long exposure would have captured +1.45% average gain.
- Total observations: 0
- First identified: 2026-01-31
Uniform Bearish Mild
Recommended approach (75% confidence, seen 1x):
Market was uniformly bearish but with mild declines (BNB -1.50%, BTC -1.18%, ETH -0.78%, SOL -2.53%, DOGE -0.81%). Best performers used moderate-frequency SHORT-biased trading (31-32 trades) with selective entries. Forum-aware sentiment filtering and agentic multi-step reasoning both profited. Momentum and contrarian strategies lost money. Zero trading preserved capital perfectly.
- Total observations: 0
- First identified: 2026-03-07
Mixed Low Volatility
Recommended approach (75% confidence, seen 1x):
Market was mixed with small daily moves (BNB -0.23%, BTC +0.30%, ETH +0.36%, SOL -0.30%, DOGE -0.48%). Best approach: selective moderate-frequency trading with sentiment/forum filtering (24-31 trades). Forum-aware's +$232.17 dominated. Avoid momentum-following and contrarian strategies which both lost money. Zero trading is safe but suboptimal when forum-aware can extract alpha.
- Total observations: 0
- First identified: 2026-03-08
Uniform Bullish Moderate
Recommended approach (75% confidence, seen 1x):
Self-reflective position management (journal-aware) is the ONLY approach that profited among active agents. Meta-cognitive exits ('we are overtrading', 'close to reduce exposure') preserved gains and limited losses from wrong-direction entries.
- Total observations: 0
- First identified: 2026-03-09
Uniform Bearish Moderate
Recommended approach (73% confidence, seen 1x):
Avoid LONG-biased strategies entirely. Momentum (+8 trades, -$34.40) and contrarian (+9 trades, -$15.04) strategies that likely entered LONGs all lost money. Even low-frequency LONG entries (qwen35_simple, 4 trades, -$99.44) suffered large losses.
- Total observations: 0
- First identified: 2026-03-06
Uniform Bearish Mild
Recommended approach (73% confidence, seen 1x):
SOL was the worst performer (-2.53%) and BNB second worst (-1.50%), making them the best SHORT targets. ETH had the smallest decline (-0.78%), making it the worst SHORT target. Focus SHORT entries on highest-beta assets.
- Total observations: 0
- First identified: 2026-03-07
Uniform Bearish Mild
Recommended approach (70% confidence, seen 1x):
Trade frequency sweet spot in this mild bearish window was 31-32 trades/24h. Below that (11 trades contrarian) still lost money due to wrong direction. Above that is not represented. The key differentiator was directional alignment (SHORT bias) combined with selective entry filtering.
- Total observations: 0
- First identified: 2026-03-07
Mixed Low Volatility
Recommended approach (70% confidence, seen 1x):
In low-volatility mixed markets, trade frequency sweet spot is 24-31 trades/24h. Below that (2-16 trades) either breaks even or loses small amounts. Above that (33 trades for momentum) loses more. The key differentiator is signal quality, not frequency.
- Total observations: 0
- First identified: 2026-03-08
Uniform Bearish
Recommended approach (65% confidence, seen 1x):
Focus shorts on highest-volatility losers: ETHUSDT (-2.31%) offered best short opportunity vs SOLUSDT (-1.31%). Volatility creates profit potential.
- Total observations: 0
- First identified: 2026-01-30
Uniform Bearish Moderate
Recommended approach (65% confidence, seen 1x):
HIGH-frequency SHORT-biased trading with self-reflective position management (30-48 trades/24h). Journal-aware's 48 trades (+$296.01) and agentic's 30 trades (+$193.68) both profited by aligning with the bearish trend. Self-reflective exits helped capture profits and limit drawdowns. This CONTRADICTS prior patterns suggesting ultra-low frequency is optimal in bearish markets — when agents correctly identify the bearish regime, higher frequency with SHORT bias is profitable.
- Total observations: 0
- First identified: 2026-03-06
Uniform Bearish Moderate
Recommended approach (60% confidence, seen 1x):
Focus SHORT entries on highest-beta assets. ETHUSDT (-4.72%) and SOLUSDT (-4.40%) had the largest declines, offering the most profit potential. BTCUSDT (-4.29%) was also a strong SHORT candidate. BNBUSDT (-2.99%) had the smallest decline.
- Total observations: 0
- First identified: 2026-03-06
Uniform Bearish Moderate
Recommended approach (55% confidence, seen 1x):
Ultra-low frequency trading (13-16 trades/24h) with simple strategies. Market was uniformly bearish (BNB -1.70%, BTC -3.47%, ETH -4.63%, SOL -4.70%, DOGE -8.71%). Only qwen35 simple models profited. Zero trading also preserved capital. Avoid high-frequency trading (27-62 trades) which amplified losses. DOGE had the largest decline (-8.71%), making it the highest-beta SHORT target.
- Total observations: 0
- First identified: 2026-03-05
Uniform Bearish Moderate
Recommended approach (52% confidence, seen 1x):
If trading actively, cap at 16 trades/24h maximum. qwen35_122b_simple's 16 trades (+$50.27) was the sweet spot. Above 20 trades, all agents lost money. The relationship: 0 trades = $0, 13-16 trades = +$35-50, 14 trades (ta_bot) = -$64, 24 trades = -$6, 27 trades = -$229, 62 trades = -$71.
- Total observations: 0
- First identified: 2026-03-05
Uniform Bearish Moderate
Recommended approach (48% confidence, seen 1x):
Focus SHORT entries on highest-beta assets. DOGE (-8.71%) had nearly 5x the decline of BNB (-1.70%). SOL (-4.70%) and ETH (-4.63%) were also strong SHORT candidates. BNB was the most resilient, suggesting it should be avoided for SHORT entries.
- Total observations: 0
- First identified: 2026-03-05
Uniform Bullish
Recommended approach (47% confidence, seen 1x):
Passive index fund allocation or zero trading. When ALL assets are positive (BNB +1.23%, BTC +1.49%, ETH +1.08%, SOL +0.22%, DOGE +0.26%), active trading destroys value through transaction costs. index_fund achieved $0.00 vs -$134.51 for most active trader
- Total observations: 0
- First identified: 2026-01-28
Uniform Bullish
Recommended approach (45% confidence, seen 1x):
If trading, use extremely low frequency (<10 trades/24h) and hold positions longer. The 8 trades from index_fund vs 166 from agentic_gptoss shows 20x frequency difference with $134.51 performance gap
- Total observations: 0
- First identified: 2026-01-28
Uniform Bullish Strong
Recommended approach (45% confidence, seen 1x):
ZERO shorting rule. When ALL 5 assets gain >5% in 24h, any short position is catastrophic. This single rule would have prevented ~$838 in combined losses from gptoss_agentic and gptoss_forum_aware.
- Total observations: 0
- First identified: 2026-03-04
Mixed Slightly Bullish
Recommended approach (43% confidence, seen 1x):
Technical analysis baseline with moderate frequency (30-40 trades/24h) outperforms LLM-based multi-timeframe analysis. ta_baseline lost only $45.95 vs $134.51 for agentic_gptoss
- Total observations: 0
- First identified: 2026-01-28
Uniform Bullish Moderate
Recommended approach (15% confidence, seen 2x):
Trade frequency inversely correlates with losses when directional bias is wrong: 0 trades = $0, 6 trades = -$22.72, 15 trades = -$25.04, 27 trades = -$86 to +$55, 30-31 trades = -$97 to -$341. Each additional wrong-direction trade costs approximately $3-11.
- Total observations: 0
- First identified: 2026-03-02
Uniform Bullish Moderate
Recommended approach (13% confidence, seen 2x):
Zero trading or ultra-low frequency LONG-only entries. Market was uniformly bullish (BNB +3.31%, BTC +2.68%, ETH +3.90%, SOL +5.07%, DOGE +2.46%). Only journal-aware with self-reflective management profited (+$55.48). All other active agents lost money, suggesting most were SHORT-biased. SOL was the best performer (+5.07%), making it the top LONG target.
- Total observations: 0
- First identified: 2026-03-02
Confidence Guide
Confidence
Interpretation
90%+
High confidence - strong historical support
70-90%
Moderate confidence - use with other signals
60-70%
Low confidence - consider as one input
<60%
Experimental - needs more data
This skill is automatically generated and updated by the Observer Agent.