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 market-top-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/market-top-detector)<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/market-top-detector"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/market-top-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/market-top-detector"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/market-top-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 | $0.00091 | $0.02209 |
| Opus 5 | $0.00046 | $0.01104 |
| Sonnet 5 | $0.00018 | $0.00442 |
| Haiku 4.5 | $0.00009 | $0.00221 |
Grade A, and why
market-top-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 13d 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
89% identical to market-top-detector — 7 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 — 196 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Market Top Detector Skill
Purpose
Detect the probability of a market top formation using a quantitative 6-component scoring system (0-100). Integrates three proven market top detection methodologies:
- O'Neil - Distribution Day accumulation (institutional selling)
- Minervini - Leading stock deterioration pattern
- Monty - Defensive sector rotation signal
Unlike the Bubble Detector (macro/multi-month evaluation), this skill focuses on tactical 2-8 week timing signals that precede 10-20% market corrections.
When to Use This Skill
English:
- User asks "Is the market topping?" or "Are we near a top?"
- User notices distribution days accumulating
- User observes defensive sectors outperforming growth
- User sees leading stocks breaking down while indices hold
- User asks about reducing equity exposure timing
- User wants to assess correction probability for the next 2-8 weeks
Japanese:
- 「天井が近い?」「今は利確すべき?」
- ディストリビューションデーの蓄積を懸念
- ディフェンシブセクターがグロースをアウトパフォーム
- 先導株が崩れ始めているが指数はまだ持ちこたえている
- エクスポージャー縮小のタイミング判断
- 今後2〜8週間の調整確率を評価したい
Prerequisites
Required:
- FMP API Key: Set
$FMP_API_KEYenvironment variable or pass--api-key. Free tier sufficient (~33 API calls per execution). - WebSearch Access: Required to collect S&P 500 breadth (50DMA %) and CBOE Put/Call ratio data.
Optional:
- Margin Debt Data: Enhances sentiment scoring but typically 1-2 months lagged.
- VIX Term Structure: Auto-detected from FMP API if VIX3M quote available; manual override via
--vix-term.
Data Freshness: All manually collected data should be from the most recent 3 business days for accurate analysis.
Difference from Bubble Detector
| Aspect | Market Top Detector | Bubble Detector |
|---|---|---|
| Timeframe | 2-8 weeks | Months to years |
| Target | 10-20% correction | Bubble collapse (30%+) |
| Methodology | O'Neil/Minervini/Monty | Minsky/Kindleberger |
| Data | Price/Volume + Breadth | Valuation + Sentiment + Social |
| Score Range | 0-100 composite | 0-15 points |
What ships with it
37 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/distribution_day_guide.md 4.3 KB
- references/historical_tops.md 6.9 KB
- references/market_top_methodology.md 7.1 KB
- scripts/breadth_csv_client.py 3.5 KB runs code
- scripts/calculators/__init__.py 732 B runs code
- scripts/calculators/breadth_calculator.py 3.8 KB runs code
- scripts/calculators/defensive_rotation_calculator.py 7.1 KB runs code
- scripts/calculators/distribution_day_calculator.py 6.4 KB runs code
- scripts/calculators/index_technical_calculator.py 7.4 KB runs code
- scripts/calculators/leading_stock_calculator.py 9.3 KB runs code
- scripts/calculators/math_utils.py 1.5 KB runs code
- scripts/calculators/sentiment_calculator.py 6.9 KB runs code
- scripts/fmp_client.py 19 KB runs code
- scripts/historical_comparator.py 3.8 KB runs code
- scripts/market_top_detector.py 23 KB runs code
- scripts/report_generator.py 17 KB runs code
- scripts/scenario_engine.py 4.2 KB runs code
- scripts/scorer.py 20 KB runs code
- scripts/tests/conftest.py 307 B runs code
- scripts/tests/helpers.py 1.4 KB runs code
- scripts/tests/test_breadth_csv_client.py 3.8 KB runs code
- scripts/tests/test_breadth.py 2.5 KB runs code
- scripts/tests/test_defensive_rotation.py 5.1 KB runs code
- scripts/tests/test_delta.py 4.5 KB runs code
- scripts/tests/test_distribution_day.py 6.4 KB runs code
- scripts/tests/test_fmp_client.py 27 KB runs code
- scripts/tests/test_freshness.py 4.1 KB runs code
- scripts/tests/test_historical_comparator.py 2.8 KB runs code
- scripts/tests/test_index_technical.py 2.9 KB runs code
- scripts/tests/test_leading_stock.py 9.2 KB runs code
- scripts/tests/test_math_utils.py 2.7 KB runs code
- scripts/tests/test_report_generator.py 7.5 KB runs code
- scripts/tests/test_scenario_engine.py 3.5 KB runs code
- scripts/tests/test_scorer.py 17 KB runs code
- scripts/tests/test_sentiment.py 3.6 KB runs code
- scripts/tests/test_utils.py 1.6 KB runs code
- scripts/utils.py 612 B 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.
- 13d ago First seen · 196 lines · 91 tokens per session scan A 804ae19fcff7
market-top-detector is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 9d ago), licensed MIT. It adds 91 tokens to every session and 2,209 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to market-top-detector, differing in 7 lines, and is treated as a copy.
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