trading-signals
Provides multi-asset trading signals based on various trading system patterns, combining quantitative and social sentiment analysis.
npx skills add scientiacapital/skills --skill trading-signalsBefore / After Comparison
1 组Difficulty in acquiring real-time multi-asset trading signals, coupled with a lack of quantitative and social sentiment analysis support, leads to subjective and high-risk trading decisions and unstable returns.
Based on various trading system models, it provides multi-asset trading signals, combining quantitative and social sentiment analysis to significantly enhance the objectivity and success rate of trading decisions.
description SKILL.md
trading-signals
Built on patterns from ThetaRoom (50K+ lines, 7-layer MasterQuantAgent), SwaggyStacks (Markov trading system), and SignalSiphon (social sentiment pipeline).
<quick_start> Multi-asset analysis — start with regime, then route by asset class:
-
Identify regime → Markov 7-state model (see
reference/markov-regime.md) -
Route by asset → Options? Stocks? Crypto? Commodities? VIX? Forex?
-
Apply methodologies → Confluence scoring with regime-weighted fusion
-
Size the position → Risk management (max 2% per trade, 15% portfolio)
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Explain the why → Educational mode: every signal comes with reasoning
Confluence score:
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0.7-1.0: High conviction → execute with full position
-
0.4-0.7: Moderate → wait for more confluence or reduce size
-
0.0-0.4: No trade → stay patient
Quick options analysis:
Ticker + Strike + Expiry → Greeks profile → Strategy fit → Risk/reward → Go/No-go
</quick_start>
<success_criteria> Analysis is successful when:
-
Regime identified first (always — this determines methodology weights)
-
Asset class correctly routed to relevant reference material
-
Multiple methodologies provide confluence (not just one signal)
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Options trades include full Greeks breakdown (delta, gamma, theta, vega minimum)
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Position sized with risk management (max 2% per trade, 8% drawdown halt)
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Educational "why" provided — the reasoning behind the signal, not just the signal
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Clear action: BUY/SELL/HOLD/ROLL/CLOSE with specific levels
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NO OPENAI in model routing — use DeepSeek/Qwen for bulk, Claude for decisions </success_criteria>
<asset_routing> Route the user's question to the right analysis framework. Most questions involve multiple assets — use all relevant references.
Asset Class Router
User Mentions Primary Reference Also Load
Options, Greeks, iron condor, spreads, calls, puts, strikes, IV, DTE
options-trading.md + options-strategies.md
vix-volatility.md for IV context
Stocks, equities, AAPL, SPY, sectors, earnings
equities.md
TA methodologies as needed
Bitcoin, crypto, BTC, ETH, on-chain, halving
elliott-wave.md + markov-regime.md
options-trading.md if BTC options
Gold, silver, oil, commodities, crude, WTI
commodities.md
fibonacci.md for levels
VIX, volatility, IV rank, vol surface
vix-volatility.md
options-trading.md for vol trades
Forex, FX, EUR/USD, carry trade, central bank
forex.md
markov-regime.md for regime
Sentiment, Twitter, Reddit, social signals
sentiment-signals.md
Asset-specific ref
Position sizing, risk, drawdown, portfolio
risk-management.md
Asset-specific ref
Daily prep, pre-market, market open, EOD review
daily-trading-workflow.md
Asset-specific refs
Backtest, walk forward, monte carlo, strategy test
backtesting-patterns.md
Strategy-specific refs
General TA, chart, pattern, support/resistance
pattern-recognition.md
fibonacci.md, wyckoff.md
Breakout, trend following, Donchian, ATR, pyramiding
turtle-trading.md
markov-regime.md for regime
Accumulation, distribution, Wyckoff, VSA, composite operator
wyckoff.md
pattern-recognition.md
Multi-LLM consensus, swarm voting, model agreement
swarm-consensus.md
Asset-specific ref
Chinese LLMs, DeepSeek, Qwen, cost routing, budget
chinese-llm-stack.md
swarm-consensus.md
When Multiple Assets Interact
Many real trades span asset classes. Examples:
-
"VIX spiked, should I adjust my SPY iron condor?" →
vix-volatility.md+options-strategies.md+risk-management.md -
"Gold is rallying, what does that mean for crypto?" →
commodities.md+ correlation analysis +markov-regime.md -
"My AAPL calls are deep ITM before earnings" →
options-trading.md+equities.md+risk-management.md</asset_routing>
<educational_mode> Every analysis should teach, not just tell. Follow this pattern:
Signal → Why → Context → Action
Example: "The iron condor makes sense here because IV rank is at 78% — that's top quartile, meaning options premiums are historically expensive. You're selling that rich premium. Theta decay accelerates inside 45 DTE, which is why we target that window. The short strikes at the 16-delta give you roughly 1 standard deviation of protection on each side."
Principles:
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Explain the market structure driving the signal (regime, vol environment, flow)
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Connect Greeks to real P&L impact ("your theta is -$45/day, meaning you earn $45 if nothing moves")
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Reference historical patterns when relevant ("Bitcoin post-halving typically enters Bull Quiet regime within 6 months")
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Flag what could go wrong and why ("if VIX breaks 35, the regime shifts to crisis mode and your iron condor wings are at risk") </educational_mode>
<core_analysis>
Technical Analysis Methodologies
The foundation — 5 TA methodologies with regime-weighted confluence scoring.
Methodology Purpose Best Regime Weight (Trending)
Elliott Wave Wave position + targets Trending 0.30
Turtle Trading Breakout + trend follow Trending 0.30
Fibonacci Support/resistance zones Ranging/Volatile 0.20-0.35
Wyckoff Institutional accumulation/distribution Ranging 0.15-0.30
Markov Regime State classification Always first Determines weights
Confluence Detection
class ConfluenceAnalyzer:
"""Regime-weighted methodology fusion — from ThetaRoom MasterQuantAgent"""
REGIME_WEIGHTS = {
'trending_up': {'elliott': 0.30, 'turtle': 0.30, 'fib': 0.20, 'wyckoff': 0.15},
'trending_down': {'elliott': 0.30, 'turtle': 0.30, 'fib': 0.20, 'wyckoff': 0.15},
'ranging': {'fib': 0.35, 'wyckoff': 0.30, 'elliott': 0.20, 'turtle': 0.05},
'volatile': {'fib': 0.30, 'wyckoff': 0.30, 'elliott': 0.20, 'turtle': 0.10},
}
Score → Action:
-
0.7-1.0: High conviction entry (full position)
-
0.4-0.7: Wait for more confluence (half position or watch)
-
0.0-0.4: No trade (patience pays)
MasterQuantAgent Ensemble (ThetaRoom v1)
7-layer weighted voting for highest-conviction decisions:
Layer Weight What It Checks
Golden Pocket (Fib 0.618-0.65) 0.20 Institutional accumulation zone
Swarm Consensus 0.20 Multi-LLM agreement
Elliott Wave 0.15 Wave structure and targets
Methodology Specific 0.15 Strategy-specific signal
Wyckoff LSTM 0.10 Accumulation phase ML
Microstructure 0.10 Order flow + dark pool
Sentiment 0.10 News + social scoring
8-Node Trading Pipeline (ThetaRoom v2)
Scanner → Volatility → Greeks → Risk → Entry → Position → Execution → Exit
Each node maps to a LangGraph agent. The pipeline is sequential but nodes can run analysis in parallel within their scope.
Cost-Effective Model Routing
Task Model Cost/1M
Pattern detection, scanning DeepSeek-V3 $0.27
Confluence scoring Qwen-72B $0.40
Critical trading decisions Claude Sonnet $3.00
Swarm consensus Mixed tier ~$1.50 avg
Architecture/strategy design Claude Opus $5.00
</core_analysis>
<project_integration>
ScientiaCapital Trading Ecosystem
Project Path Use For
ThetaRoom v1
~/Desktop/tk_projects/theta-room/
Production reference: methodologies, options services, risk management, brokers
ThetaRoom v2
~/Desktop/tk_projects/thetaroom/
Architecture blueprint: NautilusTrader, config thresholds, agent design
SwaggyStacks
~/Desktop/tk_projects/swaggy-stacks/
Options strategies, Markov model, Greeks-Fib fusion, backtesting
SignalSiphon
~/Desktop/tk_projects/signal-siphon/
Sentiment pipeline, social signal filtering
research-hub
scientiacapital/research-hub
Multi-agent research with /trading, /market commands
model-finops
scientiacapital/model-finops
Intelligent LLM router (60% cost reduction)
silkroute
scientiacapital/silkroute
Chinese LLM orchestrator, 3-tier budget governance
Key code references:
-
Options Greeks:
theta-room/backend/nautilus/greeks_actor.py -
12 options strategies:
swaggy-stacks/backend/app/strategies/options/ -
Markov 7-state:
swaggy-stacks/backend/app/methodologies/bitcoin/ -
Risk config:
thetaroom/thetaroom/config.py(ThetaRoomConfig) -
Sentiment:
signal-siphon/backend/analyzer/sentiment_analyzer.py -
Brokers:
theta-room/backend/brokers/(Alpaca, Binance, IBKR, Deribit, Polymarket)
Data sources in your stack:
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Polygon.io / Massive — real-time stocks, options, crypto, forex
-
yfinance — historical OHLCV
-
Alpaca SDK — stock/options/crypto trading + data
-
Binance — spot, futures (USD-M, COIN-M), options
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Deribit — BTC options (~90% market share)
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CoinGecko — crypto prices (free tier)
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NautilusTrader — execution engine (ThetaRoom v2) </project_integration>
<reference_files>
Reference Files
Technical Analysis Methodologies:
-
reference/elliott-wave.md— Wave rules, halving supercycle, crypto adaptation, targets -
reference/turtle-trading.md— Donchian channels, ATR sizing, pyramiding -
reference/fibonacci.md— Levels, golden pocket, Greeks-Fib fusion, on-chain enhanced -
reference/wyckoff.md— Phase state machines, VSA, composite operator -
reference/markov-regime.md— 7-state model, transition probabilities, regime-based signals
Options & Volatility:
-
reference/options-trading.md— Greeks (1st + 2nd order), Black-Scholes, IV surface, vol smile, GEX, pin risk -
reference/options-strategies.md— 25+ strategies: income, directional, volatility, advanced multi-leg -
reference/vix-volatility.md— IV rank, VIX term structure, crisis thresholds, regime integration
Asset Classes:
-
reference/equities.md— Sector rotation, scanner patterns, Kelly allocation, earnings plays -
reference/commodities.md— Gold/Silver (COT, seasonal, dollar correlation), Oil (inventory, OPEC, contango) -
reference/forex.md— Carry trade, rate differentials, PPP, central bank policy, COT positioning
Cross-Cutting:
-
reference/sentiment-signals.md— Social filtering, multi-model consensus, noise detection -
reference/risk-management.md— Position sizing, portfolio Greeks gates, drawdown limits, smart execution -
reference/pattern-recognition.md— Candlestick + chart patterns -
reference/swarm-consensus.md— Multi-LLM voting system -
reference/chinese-llm-stack.md— Cost-optimized Chinese LLMs for trading
Workflow & Backtesting:
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reference/daily-trading-workflow.md— /loop + Desktop scheduled tasks for pre-market, open, intraday, EOD -
reference/backtesting-patterns.md— Walk-forward, Monte Carlo, ensemble, combinatorial alpha discovery </reference_files>
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