parabolic-short-trade-planner
Screen US equities for parabolic exhaustion patterns and generate conditional pre-market short plans, then evaluate intraday trigger fires from live 5-min bars. Phase 1 daily 5-factor scorer (MA extension / acceleration / volume climax / range expansion / liquidity), Phase 2 per-candidate plans for ORL break / first-red 5-min / VWAP fail with explicit borrow / SSR / manual-confirmation gating, Phase 3 one-shot intraday FSM that detects trigger fires and resolves concrete share counts. Covers Phase 1 + Phase 2 + Phase 3.
npx skills add BaggaT236/AI-Trading-Skills --skill parabolic-short-trade-planner --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
## Overview 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: - **Phase 1 (`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. - **Phase 2 (`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. - **Phase 3 (`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. ## When to Use Invoke this skill wh
- Overview
- When to Use
- Workflow
- Phase 1 — daily screener
- Phase 2 — pre-market plan generator
- Phase 3 — intraday trigger monitor
- Reviewing a plan before entry
- Earnings-aware screening
- Output Format
- Resources
python3 skills/parabolic-short-trade-planner/scripts/screen_parabolic.py \ python3 skills/parabolic-short-trade-planner/scripts/generate_pre_market_plan.py \ python3 skills/parabolic-short-trade-planner/scripts/monitor_intraday_trigger.py \
What does the parabolic-short-trade-planner skill do?
Screen US equities for parabolic exhaustion patterns and generate conditional pre-market short plans, then evaluate intraday trigger fires from live 5-min bars. Phase 1 daily 5-factor scorer (MA extension / acceleration / volume climax / range expansion / liquidity), Phase 2 per-candidate plans for ORL break / first-red 5-min / VWAP fail with explicit borrow / SSR / manual-confirmation gating, Phase 3 one-shot intraday FSM that detects trigger fires and resolves concrete share counts. Covers Phase 1 + Phase 2 + Phase 3.
How do I install it?
Run `npx skills add BaggaT236/AI-Trading-Skills --skill parabolic-short-trade-planner --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BaggaT236/AI-Trading-Skills, a repository with 118 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.