Agent-Skills.md

Agent Skills: FTD Detector Skill

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).

UncategorizedID: tradermonty/claude-trading-skills/ftd-detector
17649

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pnpm dlx add-skill https://github.com/tradermonty/claude-trading-skills/tree/HEAD/skills/ftd-detector

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skills/ftd-detector/SKILL.md

Skill Metadata

Name
ftd-detector
Description
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).

FTD Detector Skill

Purpose

Detect Follow-Through Day (FTD) signals that confirm a market bottom, using William O'Neil's proven methodology. Generates a quality score (0-100) with exposure guidance for re-entering the market after corrections.

Complementary to Market Top Detector:

  • Market Top Detector = defensive (detects distribution, rotation, deterioration)
  • FTD Detector = offensive (detects rally attempts, bottom confirmation)

When to Use This Skill

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

Difference from Market Top Detector

| Aspect | FTD Detector | Market Top Detector | |--------|-------------|-------------------| | Focus | Bottom confirmation (offensive) | Top detection (defensive) | | Trigger | Market correction (3%+ decline) | Market at/near highs | | Signal | Rally attempt → FTD → Re-entry | Distribution → Deterioration → Exit | | Score | 0-100 FTD quality | 0-100 top probability | | Action | When to increase exposure | When to reduce exposure |

Execution 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

State Machine

NO_SIGNAL → CORRECTION → RALLY_ATTEMPT → FTD_WINDOW → FTD_CONFIRMED
                ↑              ↓               ↓              ↓
                └── RALLY_FAILED ←─────────────┘     FTD_INVALIDATED

| State | Definition | |-------|-----------| | NO_SIGNAL | Uptrend, no qualifying correction | | CORRECTION | 3%+ decline with 3+ down days | | RALLY_ATTEMPT | Day 1-3 of rally from swing low | | FTD_WINDOW | Day 4-10, waiting for qualifying FTD | | FTD_CONFIRMED | Valid FTD signal detected | | RALLY_FAILED | Rally broke below swing low | | FTD_INVALIDATED | Close below FTD day's low |

Quality Score (0-100)

| Score | Signal | Exposure | |-------|--------|----------| | 80-100 | Strong FTD | 75-100% | | 60-79 | Moderate FTD | 50-75% | | 40-59 | Weak FTD | 25-50% | | <40 | No FTD / Failed | 0-25% |

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).

Output Files

  • JSON: ftd_detector_YYYY-MM-DD_HHMMSS.json
  • Markdown: ftd_detector_YYYY-MM-DD_HHMMSS.md

Reference Documents

skills/ftd-detector/references/ftd_methodology.md

  • O'Neil's FTD rules in detail
  • Rally attempt mechanics and day counting
  • Historical FTD examples (2020 March, 2022 October)

skills/ftd-detector/references/post_ftd_guide.md

  • Post-FTD distribution day failure rates
  • Power Trend definition and conditions
  • Success vs failure pattern comparison

When to Load References

  • First use: Load skills/ftd-detector/references/ftd_methodology.md for full understanding
  • Post-FTD questions: Load skills/ftd-detector/references/post_ftd_guide.md
  • Regular execution: References not needed - script handles analysis