
A three-phase workflow for building Qullamaggie-style parabolic short watchlists with explicit pre-market planning and intraday trigger monitoring. Phase 1 scores S&P 500 stocks on five exhaustion factors using FMP data, Phase 2 generates conditional entry plans with borrow and SSR checks, and Phase 3 walks a finite state machine through live 5-minute bars to detect trigger fires. The design is detection-only: it never sends orders, just emits JSON with concrete share counts when a trigger condition hits. Useful if you trade parabolic exhaustion shorts and want systematic screening plus replay-deterministic monitoring that you can audit before manually pulling the trigger at your broker. The earnings-aware filtering and idempotent state management are thoughtful touches.
$ npx -y skills add tradermonty/claude-trading-skills --skill parabolic-short-trade-planner --agent claude-codeInstalls into .claude/skills of the current project.
Generate Qullamaggie-style Parabolic Short watchlists and conditional pre-market plans for US equities. The skill never sends orders. It emits JSON + Markdown that a human reviews against their broker before entry.
Three phases:
screen_parabolic.py): pulls EOD bars + company profile
from FMP, applies hard invalidation rules (mode-aware), scores
survivors on 5 factors (weights 30/25/20/15/10), and assigns A/B/C/D
grades.generate_pre_market_plan.py): takes the Phase 1 JSON,
filters by --tradable-min-grade (default B), checks Alpaca short
inventory (or ManualBrokerAdapter), evaluates SEC Rule 201 SSR
state from the inherited prior-day close, and renders three trigger
plans per candidate.monitor_intraday_trigger.py): reads the Phase 2 plan,
fetches 5-min bars (Alpaca live or fixture), walks each plan's FSM
forward by one step, persists per-plan state, and writes an
intraday_monitor JSON with state, entry_actual, stop_actual,
and shares_actual (when triggered). One-shot — trader runs it
every 1–5 min via watch or cron; replay-deterministic so re-runs
are byte-identical.Sponsors