minervini-vcp

minervini-vcp is a skill for Claude Code, Codex from questflowai/investorskills. It costs 40 tokens per session (557 once invoked), scanned A, original, MIT.

A stock-chart review method for finding Minervini-style Volatility Contraction Patterns (VCPs), where price pulls back less and less before a possible breakout. It checks trends, moving averages, relative strength, volume, and risk levels.

In plain words
What is it for?
Use it to review growth-stock bases, identify a potential breakout pivot, check whether trading volume supports the move, and plan an entry, stop, or position addition.
Why use it?
It helps organize several chart signals into one consistent setup review, so you can avoid treating every breakout as a promising trade.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to review growth-stock bases, identify a potential breakout pivot, check whether trading volume supports the move, and plan an entry, stop, or position addition.

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Install with agentmods
npx agentmods add skills/questflowai/investorskills/minervini-vcp
About the project

Investor Skills is an open-source library that organizes investing judgment—such as evaluating opportunities, managing risk, and acting under uncertainty—into structured, reusable instructions for people and AI finance agents. It is designed for studying and applying investment approaches, including inside Questflow and other agent tools. The catalogue includes portable skill packages from the library.

questflowai/investorskills · 1,849 stars · on GitHub · questflow.ai

Install

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.

Any agent
npx skills add questflowai/investorskills --skill minervini-vcp
Clone the repo
git clone --depth 1 https://github.com/questflowai/investorskills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for minervini-vcp

README.md
[![agentmods](https://agentmods.dev/badge/skills/questflowai/investorskills/minervini-vcp/github.svg)](https://agentmods.dev/skills/questflowai/investorskills/minervini-vcp)
Your own site
<a href="https://agentmods.dev/skills/questflowai/investorskills/minervini-vcp"><img src="https://agentmods.dev/badge/skills/questflowai/investorskills/minervini-vcp/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.

agentmods 80×15 button for minervini-vcp

Your own site · 80×15
<a href="https://agentmods.dev/skills/questflowai/investorskills/minervini-vcp"><img src="https://agentmods.dev/badge/skills/questflowai/investorskills/minervini-vcp.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 557 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00040 $0.00557
Opus 5 $0.00020 $0.00279
Sonnet 5 $0.00008 $0.00111
Haiku 4.5 $0.00004 $0.00056

Measured 12d ago against content hash a0ac97348a86, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

minervini-vcp 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.

skills/minervini-vcp/SKILL.md · 80 lines

How it starts

The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Minervini VCP

Use this skill to apply Mark Minervini-style Volatility Contraction Pattern analysis: find leading stocks in uptrends, wait for volatility to contract through successive pullbacks, buy the breakout through a pivot, and cut quickly if the setup fails.

When To Use

Use this skill when the user asks for:

  • VCP pattern review
  • Platform/base breakout analysis
  • Tightness and volatility contraction checks
  • Moving-average and relative-strength alignment
  • Entry, stop, and add plan for a growth leader

Trigger phrases include Minervini, VCP, volatility contraction, tightness, platform, pivot, SEPA, stage 2, and breakout.

Do Not Use When

  • The stock is below key moving averages or in a downtrend.
  • The base is wide, loose, and volatile.
  • The breakout is far extended from the pivot.
  • The user wants long-term value analysis only.

Inputs Needed

  • Ticker, timeframe, and recent OHLCV
  • Moving averages: 50-day, 150-day, 200-day if available
  • Relative strength versus market and industry
  • VCP contractions, pivot, volume dry-up, and breakout volume
  • Earnings/sales growth if available
  • Risk budget if sizing is requested

Process

  1. Confirm stage-2 uptrend and moving-average alignment.
  2. Check relative strength and leadership.
  3. Identify contraction sequence: each pullback should get smaller and tighter.
  4. Confirm volume dries up near the pivot.
  5. Define pivot, entry, stop, first add, and invalidation.
  6. Reject loose, extended, or lagging setups.

Output Format

# Minervini VCP View: [Stock]

## Verdict
Buyable Breakout / Watch Pivot / Too Loose / Extended / Failed / Pass

## Trend Template

## VCP Structure

## Pivot And Stop

## Volume And Relative Strength

## Trade Plan

## Missing Data

Guardrails

  • Do not buy loose VCPs.
  • Do not buy below declining key moving averages.
  • Do not chase far above the pivot.
  • Do not widen stops after entry.
  • Do not average down.

Questflow Use

In Questflow, this skill is best used as a technical breakout module for detecting VCP/platform setups, defining stop levels, and monitoring breakout follow-through.

Read the full file on GitHub · 80 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. 12d ago First seen · 80 lines · 40 tokens per session scan A a0ac97348a86

Subscribe to this mod's changes

minervini-vcp is a skill published in the GitHub repository questflowai/investorskills (1,849 stars, last pushed 19d ago), licensed MIT. It adds 40 tokens to every session and 557 once invoked, about $0.0002 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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