ATAS indicators and Python pipeline for trading the E-mini Nasdaq-100 (NQ) and E-mini S&P 500 (ES) futures using options-derived levels (GEX, DEX, walls, gamma flip, pin strikes) and AI-generated daily briefings.

• Python pipeline scrapes CME and CBOE option chains, computes Greeks Exposure levels (GEX, VEX, DEX, CEX), enriches with VIX and macro context, and writes a JSON file every 5 minutes during RTH.
• ATAS indicators (C#) read the JSON and draw the levels live on NQ/ES charts, with an on-chart context score, a floating panel, an intraday replay, and 12 alert types.
• AI briefing uses Claude to generate a daily JSON briefing with regime analysis, RTH plan (buy/sell zones, invalidations), and risk alerts. Rendered as a dark-theme A4 PDF.

Required path: the repository must end up at C:\OFK_Atas_GEX\ (root of the C: drive). The ATAS indicator default settings are pre-configured for this location. Installing elsewhere requires manual editing of indicator parameters in ATAS.

1. Download the source ZIP from the latest release
2. Extract it — you'll get a folder named OFK_Atas_GEX-main
3. Rename it to OFK_Atas_GEX and move it to C:\ so you have C:\OFK_Atas_GEX\
4. Install Python 3.10 or higher (tested on 3.14) if you don't have it already: download from python.org and make sure to check "Add Python to PATH" during installation. Verify it works by opening PowerShell and running python --version — you should see Python 3.10 or higher (try python3 --version if python is not recognized).
5. Open PowerShell and run:

# Copy the precompiled DLL to ATAS
Copy-Item "C:\OFK_Atas_GEX\dist\OFK_Atas_GEX.dll" "$env:APPDATA\ATAS\Indicators\" -Force

# Install Python dependencies
cd C:\OFK_Atas_GEX\OFK_GEX_Pipeline
pip install -r requirements.txt
playwright install chromium

1. Restart ATAS — indicators appear in the "Custom" category:
   • OFK NQ GEX Levels
   • OFK NQ Context Score
   • OFK ES GEX Levels
   • OFK ES Context Score

The precompiled DLL targets .NET 10 / Windows. No build tools required.

Building from source (only if you modify the C# code): see OFK_ATAS/README.md.

The package ships two indicators that work together: OFK GEX Levels (the levels and the floating panel) and OFK Context Score (a directional bias gauge). Both read the same full_levels_*.json produced by the Python pipeline.

Once OFK NQ GEX Levels (or its ES counterpart) is added to your chart, a floating panel summarizes everything you need for the session — and four buttons let you run the entire workflow without touching a terminal.

The top of the panel is a structured snapshot of the current session:

• Header banner — OPTIONS GREEKS NQ confirms the symbol and shows the trade date of the underlying option chain.
• Position sizing — Suggests a risk allocation level (100% • • • • • for normal, scaled down to 20% in stressed regimes) based on VIX, blackout, and data freshness.
• Alert stats — Counts of triggered alerts today and over the last 7 days.
• GEX / VEX / CEX / DEX block — Aggregate dealer positioning. The label (POSITIVE • pinning, NEGATIVE • amplifying, etc.) is the regime headline.
• Key structural levels — Gamma Flip, Vol Trigger, Risk Pivot, Vanna Flip, Charm Magnet, Max Pain, Expected Move range, and PCR.
• Intraday section (0-7 DTE) — IVx/IVR/Skew/Term, Call Wall, Put Wall, cTrans/pTrans, D+/D- DEX, top OI strikes — the levels that matter most for scalping.
• 0DTE section — End-of-session magnets (Max Pain, Pin Strike, Charm) plus total 0DTE OI.
• Structural section — CME 49d levels for the broader context.

The bottom of the panel has four actions that run the Python pipeline directly from ATAS:

OFK NQ Context Score (or its ES counterpart) renders in a sub-pane below the chart. It collapses the entire dealer positioning picture into a single number between −100 and +100 and explains why it landed there.

The score has five buckets, each with its own color shown as a histogram bar in the sub-pane:

Below the score, the indicator lists the reasons that drove it (e.g. CW broke • GF+ • squeeze+), so you can see at a glance which factors are dominant right now.

Each contribution is signed and capped, then summed and clamped to [−100, +100]:

• Position vs Call/Put Walls (up to ±30) — Where spot sits relative to the wall cluster. Above intraday CW = bullish; below intraday PW = bearish.
• Distance to Gamma Flip (up to ±30) — Normalized by the day's expected move. Far above GF = stronger bullish; far below = stronger bearish.
• Gamma regime tag (±20, ±5) — squeeze+, pos-gamma, neg-gamma, squeeze- based on spot's location in the gamma map.
• D+/D− DEX magnets (up to ±15) — Pull from delta-positive or delta-negative dealer hedging zones.
• Skew 25Δ (−10 if extreme, −5 if elevated) — Heavy put hedging is a bearish tilt.
• Term structure backwardation (−5) — Acute stress signal.
• Macro proximity (±5) — Small drift toward whatever the recent macro momentum favors.

When enabled (default), the score is forced to 0 under three conditions:

• VIX is in the EXTREME regime (panic or vol crush)
• A high-impact macro event is within the next 30 minutes (blackout window)
• The pipeline data is stale or missing

The score also displays a small text overlay on the chart showing the live value and tag (e.g. +51 [BULLISH]).

If you prefer to run the pipeline from the terminal — for cron jobs, headless setups, or scripting — the same scripts are directly callable:

cd C:\OFK_Atas_GEX\OFK_GEX_Pipeline
python run_morning_NQ.py
python run_morning_ES.py
python run_intraday_refresh.py NQ --loop --interval 300

• OFK_ATAS/README.md — ATAS indicators reference (and how to build from source)
• OFK_GEX_Pipeline/README.md — Python pipeline reference
• OFK_GEX_Pipeline/GUIDE_GEX_LEVELS.md — Trader's guide to reading the levels (the most important doc for traders)
• docs/integration_handoff/ — Integration contract for external consumers (7 documents)

• Windows 10 / 11
• ATAS 1.5+
• Python 3.10+
• Claude Code CLI (npm i -g @anthropic-ai/claude-code) for AI briefings

PolyForm Noncommercial 1.0.0 — see LICENSE.

This software is free for personal, educational, and non-commercial use. Commercial use requires prior written permission from the author. Contact via GitHub issues.