ftd-detector — Claude Code skill for follow-through day detection
Detects Follow-Through Day signals using William O'Neil's methodology and scores whether it's time to increase exposure after a correction.
npx skills add tradermonty/claude-trading-skills --skill ftd-detector -a claude-codeWhat ftd-detector does
The skill runs a Python script that pulls S&P 500 and QQQ history from the FMP API and feeds it through a state machine. States cover no signal, correction, rally attempt, FTD window, and confirmation. When the market drops 3% or more with three down days, the skill tracks the bounce and waits for a confirming day between day 4 and 10.
Output comes as JSON and Markdown with an FTD quality score from 0 to 100 and a recommended exposure level. A score of 80+ means a strong signal and 75–100% exposure; below 40 means no signal or a failed one.
You need an FMP API key, passed via the FMP_API_KEY environment variable or the --api-key flag. Python 3.9+ with the requests library is also required. Each run uses 4 API calls, within the free tier of 250 per day.
The skill pairs with market-top-detector: that one finds tops, this one finds bottoms. If no correction happened, FTD analysis doesn't apply and the skill points you to the top detector instead.
What it helps with
- tell whether a correction has ended and a bottom is forming
- score FTD signal quality from 0 to 100
- get a recommended exposure level after confirmation
- track market state across two indices at once
- time re-entry after a 3%+ decline
Example prompts for the agent
- Check for an FTD signal on the S&P 500 and NASDAQ
- The market dropped 5%, is it safe to add exposure?
- Run ftd-detector and show the current signal quality
How to install ftd-detector
1Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill ftd-detector -a claude-code2Manually: put the files in place
~/.claude/skills/ftd-detector/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/ftd-detector/
1Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill ftd-detector -a codex2Manually: put the files in place
.agents/skills/ftd-detector/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill ftd-detector -a cursor2Manually: put the files in place
.cursor/skills/ftd-detector/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install tradermonty/claude-trading-skills ftd-detector2Manually: put the files in place
.github/skills/ftd-detector/SKILL.md1Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill ftd-detector -a gemini-cli2Platform CLI
gemini skills install https://github.com/tradermonty/claude-trading-skills --path skills/ftd-detectorManually: put the files in place
.devin/skills/ftd-detector/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add tradermonty/claude-trading-skills --skill ftd-detector -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about ftd-detector
How do I install ftd-detector in Claude Code?
Run npx skills add tradermonty/claude-trading-skills --skill ftd-detector -a claude-code. The skill lands in ~/.claude/skills/ftd-detector/SKILL.md.
What does ftd-detector do?
It looks for Follow-Through Day signals using William O'Neil's methodology. It tracks the S&P 500 and NASDAQ, scores signal quality, and suggests an exposure level.
How is ftd-detector different from market-top-detector?
market-top-detector watches for distribution and exit signals. ftd-detector watches for bottom confirmation and re-entry timing. They complement each other: one is defensive, the other offensive.
Source text
SKILL.md · MIT
---
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:
```bash
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 3.9+:** 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
© tradermonty · MIT · tradermonty/claude-trading-skills