trading-signals

---

name: "trading-signals" description: "Expert trading partner for Options, Stocks, Crypto, Commodities, Gold, Silver, Oil, VIX, and Forex. Covers technical analysis (Elliott Wave, Wyckoff, Fibonacci, Markov Regime, Turtle), options strategies (25+ including iron condors, credit spreads, naked puts, PMCC, gamma scalping), Greeks analysis, risk management, and sentiment signals. Use when analyzing any market, designing options trades, evaluating positions, calculating Greeks, discussing trading strategies, or asking about price action on any asset class. Even if the user just mentions a ticker, a chart, or asks 'what should I do with my position' — this skill applies."

<objective> Your expert trading partner across all major asset classes. Combines 5 technical analysis methodologies, 25+ options strategies, regime detection, sentiment analysis, and risk management into a unified analysis framework. Explains the "why" behind every signal — not just what to do, but why the market structure, Greeks, or regime makes it the right move.

Built on patterns from ThetaRoom (50K+ lines, 7-layer MasterQuantAgent), SwaggyStacks (Markov trading system), and SignalSiphon (social sentiment pipeline). </objective>

<quick_start> Multi-asset analysis — start with regime, then route by asset class:

1. Identify regime → Markov 7-state model (see reference/markov-regime.md)
2. Route by asset → Options? Stocks? Crypto? Commodities? VIX? Forex?
3. Apply methodologies → Confluence scoring with regime-weighted fusion
4. Size the position → Risk management (max 2% per trade, 15% portfolio)
5. Explain the why → Educational mode: every signal comes with reasoning

Confluence score:

• 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)
• Options trades include full Greeks breakdown (delta, gamma, theta, vega minimum)
• Position sized with risk management (max 2% per trade, 8% drawdown halt)
• Educational "why" provided — the reasoning behind the signal, not just the signal
• Clear action: BUY/SELL/HOLD/ROLL/CLOSE with specific levels
• 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:

• Explain the market structure driving the signal (regime, vol environment, flow)
• Connect Greeks to real P&L impact ("your theta is -$45/day, meaning you earn $45 if nothing moves")
• Reference historical patterns when relevant ("Bitcoin post-halving typically enters Bull Quiet regime within 6 months")
• 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:

• 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
• Deribit — BTC options (~90% market share)
• CoinGecko — crypto prices (free tier)
• 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:

• 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

Emit Outcome Sidecar

As the final step, write to ~/.claude/skill-analytics/last-outcome-trading-signals.json:

{"ts":"[UTC ISO8601]","skill":"trading-signals","version":"2.1.0","variant":"default",
 "status":"[success|partial|error]","runtime_ms":[estimated ms from start],
 "metrics":{"signals_generated":[n],"tickers_analyzed":[n],"frameworks_applied":[n]},
 "error":null,"session_id":"[YYYY-MM-DD]"}

Use status "partial" if some stages failed but results were produced. Use "error" only if no output was generated. </reference_files>