Agent skill

breakout-trade-planner

Generate Minervini-style breakout trade plans from VCP screener output with worst-case risk calculation, portfolio heat management, and Alpaca-compatible order templates (stop-limit bracket for pre-placement, limit bracket for post-confirmation). Use when user has VCP screener results and wants actionable trade plans with entry/stop/target levels and position sizing.

BaggaT236github.com/BaggaT236GitHub ↗
claude-codeships scriptsMIT
Install
npx skills add BaggaT236/AI-Trading-Skills --skill breakout-trade-planner --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 9
SKILL.md size: 3 KB
Bundled scripts: yes
Path: skills/breakout-trade-planner/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 118
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Breakout Trade Planner Generate trade plans from VCP screener output following Mark Minervini's breakout methodology. Calculate position sizes using worst-case entry prices, enforce portfolio risk limits, and output Alpaca API-compatible order templates. ## When to Use - User has VCP screener JSON output and wants trade plans - User asks for breakout entry/stop/target calculation - User wants Alpaca order templates for VCP breakout candidates - User needs position sizing with portfolio heat management ## Prerequisites - VCP screener JSON output with `schema_version: "1.0"` - No API keys required (works with local JSON files) - No external skill dependencies (position sizing is built-in) ## Workflow ### Step 1: Generate Trade Plans Run the planner with VCP screener output: ```bash python3 skills/breakout-trade-planner/scripts/plan_breakout_trades.py \ --input reports/vcp_screener_YYYY-MM-DD.json \ --account-size 100000 \ --risk-pct 0.5 \ --output-dir reports/ ``` ### Step 2: Review Output Read the generated JSON and Markdown reports. Present: 1. **Actionable Orders** — Pre-breakout candidates with order templates 2. **Revalidation** — Breakout-state candidates needing live confirm

What's inside
Steps it walks through
  1. When to Use
  2. Prerequisites
  3. Workflow
  4. Step 1: Generate Trade Plans
  5. Step 2: Review Output
  6. Step 3: Explain Trade Plans
  7. Minervini Gate (Filtering Criteria)
  8. CLI Parameters
  9. Output
  10. Resources
Ships with 8 files
  • references/minervini_entry_rules.md
  • scripts/order_builder.py
  • scripts/plan_breakout_trades.py
  • scripts/risk_calculator.py
  • scripts/tests/conftest.py
  • scripts/tests/test_order_builder.py
  • scripts/tests/test_plan_breakout_trades.py
  • scripts/tests/test_risk_calculator.py
Commands it runs
python3 skills/breakout-trade-planner/scripts/plan_breakout_trades.py \
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About this skill
What does the breakout-trade-planner skill do?

Generate Minervini-style breakout trade plans from VCP screener output with worst-case risk calculation, portfolio heat management, and Alpaca-compatible order templates (stop-limit bracket for pre-placement, limit bracket for post-confirmation). Use when user has VCP screener results and wants actionable trade plans with entry/stop/target levels and position sizing.

How do I install it?

Run `npx skills add BaggaT236/AI-Trading-Skills --skill breakout-trade-planner --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From BaggaT236/AI-Trading-Skills, a repository with 118 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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