FTD Detector

Detects Follow-Through Day (FTD) signals for market bottom confirmation using William O’Neil’s methodology. Dual-index tracking (S&P 500 + NASDAQ) with state machine for rally attempt, FTD qualification, and post-FTD health monitoring. Use when user asks about market bottom signals, follow-through days, rally attempts, re-entry timing after corrections, or whether it’s safe to increase equity exposure. Complementary to market-top-detector (defensive) - this skill is offensive (bottom confirmation).

No API

Download Skill Package (.skill) View Source on GitHub

Table of Contents

1. Overview

FTD Detector Skill

2. When to Use

English:

  • User asks “Is the market bottoming?” or “Is it safe to buy again?”
  • User observes a market correction (3%+ decline) and wants re-entry timing
  • User asks about Follow-Through Days or rally attempts
  • User wants to assess if a recent bounce is sustainable
  • User asks about increasing equity exposure after a correction
  • Market Top Detector shows elevated risk and user wants bottom signals

Japanese:

  • 「底打ちした？」「買い戻して良い？」
  • 調整局面（3%以上の下落）からのエントリータイミング
  • フォロースルーデーやラリーアテンプトについて
  • 直近の反発が持続可能か評価したい
  • 調整後のエクスポージャー拡大の判断
  • Market Top Detectorが高リスク表示の後の底打ちシグナル確認

3. Prerequisites

  • FMP API Key: Required. Set FMP_API_KEY environment variable or pass via --api-key flag.
  • Python 3.8+: With requests library installed.
  • API Budget: 4 calls per execution (well within FMP free tier of 250/day).

4. Quick Start 

python3 skills/ftd-detector/scripts/ftd_detector.py --api-key $FMP_API_KEY

5. Workflow

Phase 1: Execute Python Script

Run the FTD detector script:

python3 skills/ftd-detector/scripts/ftd_detector.py --api-key $FMP_API_KEY

The script will:

  1. Fetch S&P 500 and QQQ historical data (60+ trading days) from FMP API
  2. Fetch current quotes for both indices
  3. Run dual-index state machine (correction → rally → FTD detection)
  4. Assess post-FTD health (distribution days, invalidation, power trend)
  5. Calculate quality score (0-100)
  6. Generate JSON and Markdown reports

API Budget: 4 calls (well within free tier of 250/day)

Phase 2: Present Results

Present the generated Markdown report to the user, highlighting:

  • Current market state (correction, rally attempt, FTD confirmed, etc.)
  • Quality score and signal strength
  • Recommended exposure level
  • Key watch levels (swing low, FTD day low)
  • Post-FTD health (distribution days, power trend)

Phase 3: Contextual Guidance

Based on the market state, provide additional guidance:

If FTD Confirmed (score 60+):

  • Suggest looking at leading stocks in proper bases
  • Reference CANSLIM screener for candidate stocks
  • Remind about position sizing and stops

If Rally Attempt (Day 1-3):

  • Advise patience, do not buy ahead of FTD
  • Suggest building watchlists

If No Correction:

  • FTD analysis is not applicable in uptrend
  • Redirect to Market Top Detector for defensive signals

6. Resources

References:

  • skills/ftd-detector/references/ftd_methodology.md
  • skills/ftd-detector/references/post_ftd_guide.md

Scripts:

  • skills/ftd-detector/scripts/fmp_client.py
  • skills/ftd-detector/scripts/ftd_detector.py
  • skills/ftd-detector/scripts/post_ftd_monitor.py
  • skills/ftd-detector/scripts/rally_tracker.py
  • skills/ftd-detector/scripts/report_generator.py