Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add BaggaT236/AI-Trading-Skills --skill ftd-detectorgit clone --depth 1 https://github.com/BaggaT236/AI-Trading-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/baggat236/ai-trading-skills/ftd-detector)<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/ftd-detector"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/ftd-detector/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/ftd-detector"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/ftd-detector.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00110 | $0.01413 |
| Opus 5 | $0.00055 | $0.00707 |
| Sonnet 5 | $0.00022 | $0.00283 |
| Haiku 4.5 | $0.00011 | $0.00141 |
Grade A, and why
ftd-detector scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to ftd-detector — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
- Fetch S&P 500 and QQQ historical data (60+ trading days) from FMP API
- Fetch current quotes for both indices
- Run dual-index state machine (correction → rally → FTD detection)
- Assess post-FTD health (distribution days, invalidation, power trend)
- Calculate quality score (0-100)
- Generate JSON and Markdown reports
What ships with it
12 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/ftd_methodology.md 7.2 KB
- references/post_ftd_guide.md 7.0 KB
- scripts/fmp_client.py 16 KB runs code
- scripts/ftd_detector.py 10 KB runs code
- scripts/post_ftd_monitor.py 13 KB runs code
- scripts/rally_tracker.py 19 KB runs code
- scripts/report_generator.py 16 KB runs code
- scripts/tests/conftest.py 296 B runs code
- scripts/tests/helpers.py 3.0 KB runs code
- scripts/tests/test_fmp_client.py 15 KB runs code
- scripts/tests/test_post_ftd_monitor.py 16 KB runs code
- scripts/tests/test_rally_tracker.py 20 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 150 lines · 110 tokens per session scan A 1df3f87cfe98
ftd-detector is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 8d ago), licensed MIT. It adds 110 tokens to every session and 1,413 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to ftd-detector, differing in 0 lines, and is treated as a copy.
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