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 uptrend-analyzergit 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/uptrend-analyzer)<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/uptrend-analyzer"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/uptrend-analyzer/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/uptrend-analyzer"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/uptrend-analyzer.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 | $0.00075 | $0.01398 |
| Opus 5 | $0.00037 | $0.00699 |
| Sonnet 5 | $0.00015 | $0.00280 |
| Haiku 4.5 | $0.00007 | $0.00140 |
Grade A, and why
uptrend-analyzer 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 9d 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 uptrend-analyzer — 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Uptrend Analyzer Skill
Purpose
Diagnose market breadth health using Monty's Uptrend Ratio Dashboard, which tracks ~2,800 US stocks across 11 sectors. Generates a 0-100 composite score (higher = healthier) with exposure guidance.
Unlike the Market Top Detector (API-based risk scorer), this skill uses free CSV data to assess "participation breadth" - whether the market's advance is broad or narrow.
When to Use This Skill
English:
- User asks "Is the market breadth healthy?" or "How broad is the rally?"
- User wants to assess uptrend ratios across sectors
- User asks about market participation or breadth conditions
- User needs exposure guidance based on breadth analysis
- User references Monty's Uptrend Dashboard or uptrend ratios
Japanese:
- 「市場のブレドスは健全？」「上昇の裾野は広い？」
- セクター別のアップトレンド比率を確認したい
- 相場参加率・ブレドス状況を診断したい
- ブレドス分析に基づくエクスポージャーガイダンスが欲しい
- Montyのアップトレンドダッシュボードについて質問
Prerequisites
- Python 3.9+ with the
requestslibrary (CSV parsing uses the stdlibcsv/iomodules) - Internet connection to fetch CSV data from GitHub (no API key required)
- No paid API subscriptions needed
Difference from Market Top Detector
| Aspect | Uptrend Analyzer | Market Top Detector |
|---|---|---|
| Score Direction | Higher = healthier | Higher = riskier |
| Data Source | Free GitHub CSV | FMP API (paid) |
| Focus | Breadth participation | Top formation risk |
| API Key | Not required | Required (FMP) |
| Methodology | Monty Uptrend Ratios | O'Neil/Minervini/Monty |
Execution Workflow
Phase 1: Execute Python Script
Run the analysis script (no API key needed):
python3 skills/uptrend-analyzer/scripts/uptrend_analyzer.py
The script will:
- Download CSV data from Monty's GitHub repository
- Calculate 5 component scores
- Generate composite score and reports
Phase 2: Present Results
Present the generated Markdown report to the user, highlighting:
- Composite score and zone classification
- Exposure guidance (Full/Normal/Reduced/Defensive/Preservation)
- Sector heatmap showing strongest and weakest sectors
- Key momentum and rotation signals
What ships with it
23 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/uptrend_methodology.md 13 KB
- scripts/calculators/__init__.py 40 B runs code
- scripts/calculators/historical_context_calculator.py 6.8 KB runs code
- scripts/calculators/market_breadth_calculator.py 4.9 KB runs code
- scripts/calculators/momentum_calculator.py 7.3 KB runs code
- scripts/calculators/sector_participation_calculator.py 6.5 KB runs code
- scripts/calculators/sector_rotation_calculator.py 11 KB runs code
- scripts/data_fetcher.py 7.6 KB runs code
- scripts/report_generator.py 19 KB runs code
- scripts/scorer.py 14 KB runs code
- scripts/tests/conftest.py 304 B runs code
- scripts/tests/helpers.py 3.0 KB runs code
- scripts/tests/test_data_fetcher.py 6.9 KB runs code
- scripts/tests/test_historical_context_calculator.py 5.4 KB runs code
- scripts/tests/test_market_breadth_calculator.py 6.2 KB runs code
- scripts/tests/test_momentum_calculator.py 6.4 KB runs code
- scripts/tests/test_new_features.py 19 KB runs code
- scripts/tests/test_report_generator.py 9.1 KB runs code
- scripts/tests/test_scorer.py 6.3 KB runs code
- scripts/tests/test_sector_participation_calculator.py 5.1 KB runs code
- scripts/tests/test_sector_rotation_calculator.py 7.2 KB runs code
- scripts/tests/test_uptrend_analyzer.py 6.0 KB runs code
- scripts/uptrend_analyzer.py 8.7 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.
- 9d ago First seen · 154 lines · 75 tokens per session scan A 237f2d2075f4
uptrend-analyzer is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 9d ago), licensed MIT. It adds 75 tokens to every session and 1,398 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to uptrend-analyzer, differing in 0 lines, and is treated as a copy.
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