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 vcp-screenergit 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/vcp-screener)<a href="https://agentmods.dev/skills/baggat236/ai-trading-skills/vcp-screener"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/vcp-screener/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/vcp-screener"><img src="https://agentmods.dev/badge/skills/baggat236/ai-trading-skills/vcp-screener.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 | $0.00141 | $0.02097 |
| Opus 5 | $0.00071 | $0.01048 |
| Sonnet 5 | $0.00028 | $0.00419 |
| Haiku 4.5 | $0.00014 | $0.00210 |
Grade A, and why
vcp-screener 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 vcp-screener — 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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
VCP Screener - Minervini Volatility Contraction Pattern
Screen S&P 500 stocks for Mark Minervini's Volatility Contraction Pattern (VCP), identifying Stage 2 uptrend stocks with contracting volatility near breakout pivot points.
When to Use
- User asks for VCP screening or Minervini-style setups
- User wants to find tight base / volatility contraction patterns
- User requests Stage 2 momentum stock scanning
- User asks for breakout candidates with defined risk
- User asks "find every historical VCP in " or wants to study one ticker's
past VCP setups with forward outcomes (
--history --ticker SYM)
Prerequisites
- FMP API key (set
FMP_API_KEYenvironment variable or pass--api-key) - Free tier (250 calls/day) is sufficient for default screening (top 100 candidates)
- Paid tier recommended for full S&P 500 screening (
--full-sp500)
Workflow
Step 1: Prepare and Execute Screening
Run the VCP screener script:
# Default: S&P 500, top 100 candidates
python3 skills/vcp-screener/scripts/screen_vcp.py --output-dir skills/vcp-screener/scripts
# Custom universe
python3 skills/vcp-screener/scripts/screen_vcp.py --universe AAPL NVDA MSFT AMZN META --output-dir skills/vcp-screener/scripts
# Full S&P 500 (paid API tier)
python3 skills/vcp-screener/scripts/screen_vcp.py --full-sp500 --output-dir skills/vcp-screener/scripts
Strict Mode (Minervini pure setup)
Only return stocks with valid_vcp=True AND execution_state in (Pre-breakout, Breakout):
python3 skills/vcp-screener/scripts/screen_vcp.py --strict --output-dir reports/
Historical single-ticker mode
Walk one ticker's multi-year history, detect every VCP that ever formed, and attach forward-outcome stats (breakout / stop-hit / timeout, days-to-outcome, max gain, max loss) per detection. Useful for pattern study and backtesting context — not a real-time screener.
# Default: scan ~5 years (1260 trading days), 5-day stride, 60-day outcome window
python3 skills/vcp-screener/scripts/screen_vcp.py \
--history --ticker FIX --output-dir reports/
# Custom scan length: 750 trading days (~3 years), 90-day outcome window
python3 skills/vcp-screener/scripts/screen_vcp.py \
--history 750 --ticker TSLA \
--stride-days 5 --outcome-days 90 \
--output-dir reports/
# Long scan: 10 years (2520 trading days)
python3 skills/vcp-screener/scripts/screen_vcp.py \
--history 2520 --ticker NVDA --output-dir reports/
What ships with it
24 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/fmp_api_endpoints.md 1.6 KB
- references/scoring_system.md 9.5 KB
- references/vcp_methodology.md 4.6 KB
- scripts/_fmp_compat.py 4.9 KB runs code
- scripts/calculators/__init__.py 27 B runs code
- scripts/calculators/execution_state.py 6.5 KB runs code
- scripts/calculators/forward_outcome.py 4.5 KB runs code
- scripts/calculators/pattern_classifier.py 3.2 KB runs code
- scripts/calculators/pivot_proximity_calculator.py 4.4 KB runs code
- scripts/calculators/relative_strength_calculator.py 8.7 KB runs code
- scripts/calculators/trend_template_calculator.py 9.8 KB runs code
- scripts/calculators/vcp_pattern_calculator.py 22 KB runs code
- scripts/calculators/volume_pattern_calculator.py 9.1 KB runs code
- scripts/fmp_client.py 16 KB runs code
- scripts/historical_report.py 7.3 KB runs code
- scripts/historical_scanner.py 7.6 KB runs code
- scripts/report_generator.py 15 KB runs code
- scripts/scorer.py 8.5 KB runs code
- scripts/screen_vcp.py 36 KB runs code
- scripts/tests/conftest.py 296 B runs code
- scripts/tests/test_fmp_client_historical.py 4.9 KB runs code
- scripts/tests/test_fmp_stable_migration.py 2.2 KB runs code
- scripts/tests/test_historical_vcp.py 26 KB runs code
- scripts/tests/test_vcp_screener.py 136 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 · 173 lines · 141 tokens per session scan A 7b817ba7ec2b
vcp-screener is a skill published in the GitHub repository BaggaT236/AI-Trading-Skills (121 stars, last pushed 9d ago), licensed MIT. It adds 141 tokens to every session and 2,097 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to vcp-screener, differing in 0 lines, and is treated as a copy.
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