Agent skill · AI & Agents

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).

BaggaT236github.com/BaggaT236GitHub ↗
claude-codeships scriptsMIT
Install
npx skills add BaggaT236/AI-Trading-Skills --skill ftd-detector --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 13
SKILL.md size: 5 KB
Bundled scripts: yes
Path: skills/ftd-detector/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 118
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 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 conf

What's inside
Steps it walks through
  1. Purpose
  2. When to Use This Skill
  3. Difference from Market Top Detector
  4. Execution Workflow
  5. Phase 1: Execute Python Script
  6. Phase 2: Present Results
  7. Phase 3: Contextual Guidance
  8. State Machine
  9. Quality Score (0-100)
  10. Prerequisites
  11. Output Files
  12. Reference Documents
  13. skills/ftd-detector/references/ftdmethodology.md
  14. skills/ftd-detector/references/postftdguide.md
Ships with 12 files
  • references/ftd_methodology.md
  • references/post_ftd_guide.md
  • scripts/fmp_client.py
  • scripts/ftd_detector.py
  • scripts/post_ftd_monitor.py
  • scripts/rally_tracker.py
  • scripts/report_generator.py
  • scripts/tests/conftest.py
  • scripts/tests/helpers.py
  • scripts/tests/test_fmp_client.py
  • scripts/tests/test_post_ftd_monitor.py
  • scripts/tests/test_rally_tracker.py
Commands it runs
python3 skills/ftd-detector/scripts/ftd_detector.py --api-key $FMP_API_KEY
More from AI-Trading-Skills
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About this skill
What does the ftd-detector skill do?

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).

How do I install it?

Run `npx skills add BaggaT236/AI-Trading-Skills --skill ftd-detector --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.

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