What is parabolic-short-trade-planner?

A planning tool for finding US stocks that have risen unusually fast and may be losing momentum, then preparing conditional short-trade plans. A short trade aims to profit from a price decline; the tool does not place orders.

Use it to create daily watchlists, pre-market plans with possible entry and stop conditions, and five-minute-bar monitoring that records when a planned trigger occurs.

It organizes screening, short-availability checks, trading-rule checks, and intraday trigger monitoring in one process. Human review remains necessary before any trade is entered.

parabolic-short-trade-planner — Skill for Claude Code and Codex by Bag

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add BaggaT236/AI-Trading-Skills --skill parabolic-short-trade-planner

Clone the repo

git clone --depth 1 https://github.com/BaggaT236/AI-Trading-Skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/parabolic-short-trade-planner/github.svg)](https://agentmods.dev/skills/baggat236/ai-trading-skills/parabolic-short-trade-planner)

Your own site

<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/parabolic-short-trade-planner"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/parabolic-short-trade-planner/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/parabolic-short-trade-planner"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/parabolic-short-trade-planner.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 122 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,058 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector pass 7 Sept 2026

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00122	$0.02058
Opus 5	$0.00061	$0.01029
Sonnet 5	$0.00024	$0.00412
Haiku 4.5	$0.00012	$0.00206

Measured 12d ago against content hash 76c739ae7924, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

parabolic-short-trade-planner scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

The scan reads SKILL.md. This mod also ships 41 executable files (scripts/_fmp_compat.py, scripts/adapters/__init__.py, scripts/adapters/alpaca_inventory_adapter.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/parabolic-short-trade-planner/SKILL.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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 when the user wants to:

Build a daily Parabolic Short watchlist from S&P 500 (or a custom CSV).
Translate a watchlist into pre-market trade plans with explicit borrow / SSR / state-cap gating.
Audit a candidate's blocking vs advisory manual-confirmation reasons before placing an order at Alpaca.

Do NOT invoke for:

Long-side momentum screening — use vcp-screener or canslim-screener.
1-minute / sub-minute intraday signals — Phase 3 evaluates 5-min bars only.
Live order routing — this skill is detection-only by design; Phase 3 emits a triggered state with concrete entry/stop/share count, but the trader fires the order manually.

Workflow

Phase 1 — daily screener

Confirm FMP_API_KEY is set (env var or --api-key).

Run with the safer-by-default mode:

python3 skills/parabolic-short-trade-planner/scripts/screen_parabolic.py \
  --mode safe_largecap --as-of 2026-04-30 --output-dir reports/

Inspect reports/parabolic_short_<date>.md — the watchlist is grouped by grade (A→D).
Promote interesting names to Phase 2.

Read the full file on GitHub · 172 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

12d ago First seen · 172 lines · 122 tokens per session scan A 76c739ae7924

Subscribe to this mod's changes

parabolic-short-trade-planner is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 9d ago), licensed MIT. It adds 122 tokens to every session and 2,058 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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