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 ajeeshworkspace/indian-trading-skills --skill nse-vcp-screenergit clone --depth 1 https://github.com/ajeeshworkspace/indian-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/ajeeshworkspace/indian-trading-skills/nse-vcp-screener)<a href="https://agentmods.dev/skills/ajeeshworkspace/indian-trading-skills/nse-vcp-screener"><img src="https://agentmods.dev/badge/skills/ajeeshworkspace/indian-trading-skills/nse-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/ajeeshworkspace/indian-trading-skills/nse-vcp-screener"><img src="https://agentmods.dev/badge/skills/ajeeshworkspace/indian-trading-skills/nse-vcp-screener.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00082 | $0.01180 |
| Opus 5 | $0.00041 | $0.00590 |
| Sonnet 5 | $0.00016 | $0.00236 |
| Haiku 4.5 | $0.00008 | $0.00118 |
Grade A, and why
nse-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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NSE VCP Screener
Overview
This skill screens Indian stocks (Nifty 50/200/500) for Mark Minervini's Volatility Contraction Pattern (VCP). The VCP identifies stocks in Stage 2 uptrends that are forming tightening bases with declining volume — the classic setup before a potential breakout.
The screening pipeline has 3 phases:
- Pre-filter: Quick quote-based filtering to eliminate obvious non-candidates
- Trend Template: Apply Minervini's 7-point Stage 2 criteria using 260-day histories
- VCP Detection & Scoring: Pattern analysis with 5-component composite scoring
Data Source
This screener uses yfinance with .NS suffix for NSE stocks and the niftystocks package for stock universe lists. No paid API keys required.
Execution
python3 scripts/screen_vcp.py --universe nifty500
Command-Line Arguments
| Argument | Default | Description |
|---|---|---|
--universe |
nifty50 |
Stock universe: nifty50, nifty200, nifty500, or custom |
--custom-tickers |
— | Comma-separated tickers for custom universe (e.g., RELIANCE,TCS,INFY) |
--min-contractions |
2 |
Minimum number of contractions (2-4) |
--t1-depth-min |
10 |
Minimum T1 contraction depth % |
--t1-depth-max |
40 |
Maximum T1 contraction depth % |
--contraction-ratio |
0.75 |
Each contraction must be ≤ this ratio of the previous |
--min-contraction-days |
5 |
Minimum days per contraction |
--lookback-days |
120 |
Days to look back for pattern detection |
--breakout-volume-ratio |
1.5 |
Minimum volume ratio for breakout confirmation |
--trend-min-score |
85 |
Minimum trend template score (0-100) |
--output-dir |
reports/ |
Output directory for results |
Workflow
Step 1: Execute the Screener
Run the Python script with desired parameters:
python3 skills/nse-vcp-screener/scripts/screen_vcp.py \
--universe nifty500 \
--output-dir reports/
Step 2: Review Results
What ships with it
11 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/scoring_system.md 3.6 KB
- references/vcp_methodology.md 5.1 KB
- scripts/calculators/__init__.py 0 B runs code
- scripts/calculators/pivot_proximity_calculator.py 1.3 KB runs code
- scripts/calculators/relative_strength_calculator.py 2.6 KB runs code
- scripts/calculators/trend_template_calculator.py 2.5 KB runs code
- scripts/calculators/vcp_pattern_calculator.py 5.6 KB runs code
- scripts/calculators/volume_pattern_calculator.py 1.6 KB runs code
- scripts/report_generator.py 4.4 KB runs code
- scripts/scorer.py 1.9 KB runs code
- scripts/screen_vcp.py 8.6 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.
- 12d ago First seen · 113 lines · 82 tokens per session scan A bf6d909d4a9e
nse-vcp-screener is a skill published in the GitHub repository ajeeshworkspace/indian-trading-skills (72 stars, last pushed 20d ago), licensed MIT. It adds 82 tokens to every session and 1,180 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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