Ib Pmcc Advisor skill

IB PMCC Advisor

Analyzes all PMCC (diagonal call spread) positions in the IB portfolio and provides actionable advice on the short leg: assignment risk, P&L projections per day, and ranked roll recommendations.

IB Connection

TWS or IB Gateway must be running locally with API enabled:

• Paper trading — port 7497
• Live trading — port 7496
• IB_PORT env var — default port when --port is omitted (e.g. IB_PORT=4001 for a Gateway container). Precedence: --port flag > IB_PORT > built-in default. Set it in the shell or a .env file.

Port fallback: If the configured port fails, automatically retry on the other port. If the retry succeeds, save to memory which account type worked (live/paper) and reuse it for all IB skill calls in this and future sessions — until the user explicitly asks for the other account. If both ports fail, ask the user to verify that TWS or IB Gateway is running with API access enabled.

Instructions

Step 1: Run the script

uv run python .claude/skills/ib-pmcc-advisor/scripts/pmcc_advisor.py [--port PORT] [--account ACCOUNT] [--min-roll-dte N] [--price-mode mid|last]

The script returns JSON to stdout. Parse it and use it for the response below.

Step 2: Default response — brief inline summary

Unless the user explicitly asks for a report or JSON output, respond with a concise inline summary only. No files saved.

Format:

• One line per spread: SYMBOL — short $STRIKE exp DATE (δ=X, assign=Y%) — [HOLD / ROLL to $STRIKE]
• Lead with any red flags (assignment > 40%, DTE < 7, earnings within short window).
• For flagged spreads, add one extra line with the top roll candidate and net credit.
• Clean positions: the one-line summary is enough.

Step 3: Generate files only when explicitly requested

MD report — triggered by: "save a report", "generate a report", "write a report", "markdown", "PDF".

Read .claude/skills/ib-pmcc-advisor/templates/markdown-template.md for full formatting instructions. Save to sandbox/pmcc_advisor_{ACCOUNT}_{YYYY-MM-DD}_{HHmm}.md. Use first account ID; derive timestamp from generated_at.

The report must include all sections per spread:

1. Red flags summary — assignment > 40%, DTE < 7, no rolls, earnings warnings
2. Company description — one sentence from your own knowledge (always)
3. Technical profile — RSI, MACD, EMA crossover, ADX, SMA distance, 3mo return, bullish score (only if technical data is present in conversation context; omit otherwise)
4. Spread structure table — both legs: strike, expiry, DTE, cost, current price, IV
5. Short leg risk — delta (BS + IB), assignment probability with risk label
6. Daily P&L projections — all rows: date, days to expiry, best exit spot, max P&L (mark peak row)
7. Roll candidates table — strike, expiry, DTE, delta, assign%, IV, net credit, $/day, P&L if assigned, bid/ask
8. Comparison table — current vs roll_1/2/3 side by side
9. Recommendation — hold/roll/close with reasoning

JSON output — triggered by: "save JSON", "export JSON", "save the data", "output file".

Save raw script output to sandbox/pmcc_advisor_{ACCOUNT}_{YYYY-MM-DD}_{HHmm}.json.

Arguments

Flag	Default	Description
--port	7497	IB Gateway/TWS port
--account	all	Specific account ID
--min-roll-dte	7	Minimum DTE for roll candidates
--price-mode	mid	Option price: mid (bid+ask)/2 or last
--symbols	all	Analyze only these symbols (e.g. --symbols NVDA WMT)

JSON Output Structure

{
  "generated_at": "2026-04-30 10:25 ET",
  "data_delay": "real-time",
  "accounts": ["Uxxxxxxxx"],
  "price_mode": "mid",
  "min_roll_dte": 7,
  "symbols_filter": ["NVDA", "WMT"],
  "spreads": [
    {
      "symbol": "NVDA",
      "account": "Uxxxxxxxx",
      "qty": 10,
      "underlying_price": 201.46,
      "leaps_expiry": "20260918",
      "earnings": {
        "date": "2026-05-20",
        "timing": "AMC",
        "warning_short": false,
        "warning_roll_indices": [1, 2, 3]
      },
      "long": {
        "strike": 180.0, "expiry": "20260918", "dte": 141,
        "avg_cost": 35.51, "current_price": 36.20,
        "iv_pct": 42.1, "ib_delta": 0.7821, "ib_iv_pct": 41.8
      },
      "short": {
        "strike": 210.0, "expiry": "20260618", "dte": 49,
        "premium_received": 6.88, "current_price": 5.10,
        "iv_pct": 38.5, "delta": 0.3421, "assignment_prob_pct": 28.4,
        "ib_delta": 0.3415, "ib_iv_pct": 38.2
      },
      "daily_pnl": [
        {"date": "2026-04-30", "days_to_short_expiry": 49.0, "optimal_spot": 215.20, "pnl": 1234.56},
        {"date": "2026-05-01", "days_to_short_expiry": 48.0, "optimal_spot": 214.80, "pnl": 1289.10}
      ],
      "roll_candidates": [
        {
          "strike": 215.0, "expiry": "20260717", "dte": 78,
          "price": 5.80, "delta": 0.2910, "assignment_prob": 22.5,
          "iv_pct": 37.2, "net_credit": 0.70, "profit_per_day": 0.0744,
          "pnl_if_assigned": 3580.0, "bid": 5.60, "ask": 6.00
        }
      ],
      "comparison": {
        "current":  {"strike": 210, "expiry": "20260618", "dte": 49, "delta": 0.3421, "assignment_prob": 28.4, "profit_per_day": 0.1404, "pnl_if_assigned": 1880.0},
        "roll_1":   {"strike": 215, "expiry": "20260717", "dte": 78, "delta": 0.2910, "assignment_prob": 22.5, "profit_per_day": 0.0744, "pnl_if_assigned": 3580.0}
      }
    }
  ]
}

Key Fields

• symbols_filter — list of uppercase symbols when --symbols was used; null means full portfolio
• data_delay — "real-time" if live quotes available, "stalled - using last price" if IBKR quotes unavailable
• generated_at — NY timezone timestamp
• leaps_expiry — expiry of the long leg (YYYYMMDD); all roll candidates are capped at or before this date
• earnings.date — next earnings date (YYYY-MM-DD) from Yahoo Finance; null for ETFs
• earnings.timing — "BMO" (before open) or "AMC" (after close)
• earnings.warning_short — true if earnings fall within the last 7 calendar days before short expiry
• earnings.warning_roll_indices — 1-based indices of roll candidates whose expiry window contains the earnings date
• delta / ib_delta — BS-calculated vs. IBKR model Greeks (both reported when available)
• iv_pct / ib_iv_pct — IV in percent; BS-calculated from option price vs. IBKR model Greeks
• assignment_prob_pct — N(d2): risk-neutral probability the short expires ITM
• net_credit — credit received when rolling (negative = debit); rolls with debit > $0.10/share excluded
• pnl_if_assigned — P&L if underlying finishes above short_strike at expiry: (short_strike - long_strike - long_cost + total_premium) × 100
• daily_pnl[].optimal_spot — spot price that maximises exit P&L on that day (found via numerical optimisation); increases as theta decays the short leg
• daily_pnl[].pnl — total dollars (qty × 100 contracts) at the optimal spot on that day

Roll Selection Criteria

Candidates must satisfy both:

1. Delta ≤ 0.40 (absolute cap — allows same-strike forward rolls when current short is near expiry)
2. Net credit ≥ -$0.10/share (not a large debit)

Scans the next 5 available chain expirations after the current short expiry, bounded by the LEAPS expiry.

Ranked by: delta improvement (highest weight) → net credit → DTE extension.

Example Usage

# All accounts (paper, default)
uv run python .claude/skills/ib-pmcc-advisor/scripts/pmcc_advisor.py

# Live account, 14-day minimum roll DTE, last-price mode
uv run python .claude/skills/ib-pmcc-advisor/scripts/pmcc_advisor.py --port 7496 --account Uxxxxxxxx --min-roll-dte 14 --price-mode last

# Analyze only specific symbols
uv run python .claude/skills/ib-pmcc-advisor/scripts/pmcc_advisor.py --symbols NVDA WMT

Architecture

All logic lives in src/trading_skills/broker/pmcc_advisor.py:

• Analytics functions (top half, no IBKR imports): get_option_price, calc_iv, calc_delta, calc_assignment_prob, calc_bs_price, calc_daily_pnl_table, check_earnings_warning, find_best_rolls, build_comparison_table, score_roll_candidate
• Data layer (bottom half, uses IBKR + Yahoo Finance): get_pmcc_data, _identify_pmcc_spreads, _fetch_single_option_quote, _fetch_option_quotes_batch, _get_chain_params, _fetch_earnings_dates

Reuses from src/trading_skills/broker/:

• connection.py — ib_connection, CLIENT_IDS, fetch_positions, fetch_spot_prices, normalize_positions, best_option_chain
• black_scholes.py — implied_volatility, black_scholes_price, black_scholes_delta, estimate_iv