name: openquant-trading version: 1.0.0 description: Analyze stocks, generate trading signals, manage risk, and execute paper trades using the OpenQuant MCP server triggers:

• stock analysis
• ticker analysis
• trading signal
• insider trading
• risk assessment
• portfolio
• backtest strategy
• paper trade
• buy stock
• sell stock
• position size
• market data

OpenQuant Trading Skill

When This Skill Activates

Activate this skill when the user:

• Asks about a stock or ticker (e.g., "What do you think of AAPL?")
• Wants trading signals or strategy recommendations
• Mentions insider trading, risk, VaR, or position sizing
• Wants to check their portfolio or execute a trade
• Asks about backtesting or strategy validation
• Uses terms like "analyze", "signal", "backtest", "Kelly", "insider buy"

Prerequisites

The OpenQuant MCP server must be running. Start it:

pip install openquant-cli[mcp]
openquant-mcp

MCP endpoint: http://localhost:8000/sse (SSE transport) Server name: openquant

Common Workflows

Workflow 1: Analyze a Stock

Use when: User asks about a ticker or wants a stock opinion.

1. Call openquant_analyze(ticker="SYMBOL", days=90)
2. Review the result: current_price, insider score/label, risk level, VaR, max drawdown
3. If insider score is interesting (|score| > 25), call openquant_insider_scan(ticker="SYMBOL") for detail
4. Summarize for the user: price, insider sentiment, risk level, and whether it's worth deeper investigation
5. Do NOT execute any trades — this is research mode

Workflow 2: Get a Trading Signal

Use when: User wants a buy/sell recommendation for a ticker.

1. Call openquant_strategy_list() if user doesn't specify a strategy
2. Call openquant_strategy_run(strategy_name="STRATEGY", ticker="SYMBOL")
3. Review: action (BUY/SELL/HOLD), confidence (0-100), entry_price, stop_loss, take_profit, position_size_pct, reasoning
4. If confidence < 40: tell the user the signal is weak, suggest monitoring
5. If confidence >= 40: present the signal with all details but do NOT execute without confirmation

Workflow 3: Validate a Strategy

Use when: User wants to know if a strategy works before using it.

1. Call openquant_backtest(strategy_name="STRATEGY", ticker="SYMBOL", days=252)
2. Review: total_trades, win_rate, total_return, max_drawdown, sharpe_ratio, avg_holding_days
3. Flag concerns: win_rate < 50%, max_drawdown > 20%, sharpe < 0.5
4. Present the backtest results with interpretation

Workflow 4: Execute a Trade

Use when: User explicitly wants to place a trade.

1. Call openquant_portfolio_status() to check current balance and positions
2. Call openquant_analyze(ticker="SYMBOL") for the current price
3. Call openquant_strategy_run(strategy_name="STRATEGY", ticker="SYMBOL") for a signal
4. Call openquant_risk_assessment(tickers="SYMBOL", days=252) — MANDATORY before execution
5. Present full trade plan to user: action, shares, price, total cost, risk metrics
6. Get explicit user confirmation (e.g., "Should I execute this trade?")
7. Only if confirmed: call openquant_trade_execute(action="BUY", ticker="SYMBOL", shares=N, price=X)
8. Call openquant_portfolio_status() to confirm the trade went through

Workflow 5: Portfolio Review

Use when: User wants to check their portfolio or recent trades.

1. Call openquant_portfolio_status() for current state
2. Call openquant_trade_history(limit=20) for recent trades
3. Summarize: total value, P&L, position breakdown, recent activity

Tool Reference

Signal Interpretation

Strategy Results

• action: BUY / SELL / HOLD
• confidence: 0-100. Only trade if >= 40.
• position_size_pct: Already 0.25x Kelly, capped at 10%. Trust this value.

Agent Signals (-1.0 to +1.0)

• +0.3: BULLISH | -0.3 to +0.3: NEUTRAL | < -0.3: BEARISH

Insider Scores (-100 to +100)

• = +60: STRONG BUY | >= +25: BUY | -24 to +24: NEUTRAL | <= -25: SELL | <= -60: STRONG SELL

Risk Rules

1. 0.25x Kelly only — position_size_pct from tools is already quarter-Kelly. Do not scale up.
2. 10% max position — never exceed 10% of portfolio in one ticker. System enforces this.
3. Confidence >= 40 — do not trade on weak signals.
4. Risk assessment required — always call openquant_risk_assessment before openquant_trade_execute.
5. Multi-factor alignment — prefer when 2+ agents agree on direction.

QuantFetch Data Units

When reading data from QuantFetch (optional, requires QUANTFETCH_API_KEY):

Common Pitfalls

1. Forgetting risk assessment before trades — This is the #1 mistake. Always run openquant_risk_assessment before openquant_trade_execute. No exceptions.
2. Overriding Kelly sizing — The position_size_pct from strategy results is already 0.25x Kelly. Do not multiply it by 4 or use full Kelly. Quarter-Kelly is deliberate to reduce drawdowns.
3. Trading on low confidence — Confidence < 40 means HOLD. Don't execute just because the user is enthusiastic. Explain that the signal is weak and suggest monitoring.
4. Ignoring risk level — If openquant_risk_assessment returns risk_level = "HIGH", flag this clearly to the user before proceeding. Consider reducing position size further.
5. Mixing up data units — QuantFetch reports EPS in cents and revenue in thousands. Always divide: EPS/100, revenue/1000 before presenting to users.
6. Executing without confirmation — Even in paper mode, always show the trade plan and get explicit confirmation before calling openquant_trade_execute.
7. Treating agent signals as strategy signals — Agent signals are -1.0 to +1.0 (5 agents). Strategy confidence is 0-100 (combined result). They are different scales. Don't compare them directly.
8. Forgetting to check existing positions — Before buying, call openquant_portfolio_status to see if you already hold the ticker. Avoid doubling up unintentionally.
9. Using the wrong strategy for the situation — earnings-surge is for earnings season, not random entry. value-deep is for long-term holds, not quick trades. Match strategy to the user's intent.
10. Not backtesting — Before trusting a strategy's signals, run openquant_backtest to verify it has a positive expected return. A strategy that generates lots of BUY signals with a 30% win rate will lose money.

Strategies