risk based position sizing builder
Converts risk parameters into deterministic position-sizing logic and code for systematic trading.
$5
Works with the AI tools you already use
Claude Code
Cursor
Codex CLI
GitHub Copilot
Gemini CLI+20 moreClaude CodeCursorCodex CLIGitHub CopilotGemini CLI
OpenClaw
Manus
Grok+17 agentsrisk based position sizing builder
Example session with this skill installed
Calculate the position size for a stock trade. Equity is 50,000 USD, risk 1%, entry 150.00, stop 145.00. Give me a Python function.
- Read your context and instructions
- Compiled the risk based position
Risk Amount: 500 USD
Stop Distance: 5.00
Position Size: 100 shares
def get_size(entry=150.0, stop=145.0, equity=50000, risk_pct=1.0):
risk_amt = equity * (risk_pct / 100)
size = risk_amt / abs(entry - stop)
return int(size)
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
The problem
Traders often struggle to translate abstract risk management rules into precise, executable position sizes across different asset classes. Manual calculations for futures multipliers or forex pip values are prone to human error, leading to over-leveraged accounts or broken strategy logic.
What it does
- Calculates exact position sizes for stocks, futures, forex, and crypto based on account equity and stop loss distance.
- Generates reusable Excel/Google Sheets formulas for dynamic sizing models.
- Outputs production-ready Python or JavaScript functions for automated trading bots.
- Applies strategy-specific constraints like max exposure caps, pyramiding rules, and correlation filters.
- Validates inputs to ensure stop distances are non-zero and risk percentages are positive.
Frameworks & tools
Python, JavaScript, Excel, Google Sheets.
Why this beats prompting it yourself
General LLMs often forget to account for contract multipliers in futures or specific lot step rounding in forex. This skill uses deterministic formulas to ensure financial accuracy, preventing the "hallucinated" math that ruins trading accounts.
Use cases
- Building a risk management module for a Python-based algorithmic trading bot.
- Creating a dynamic position-sizing calculator in a Google Sheets trading journal.
- Auditing existing strategy code to ensure it respects portfolio-wide risk limits.
- Converting complex pyramiding rules into code-based execution logic.
Known limitations
Does not handle nonlinear payoffs for options without delta-adjustment inputs. Requires manual entry of current account equity and instrument-specific values like pip cost.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.
- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
Skills folder by agent
Click the path to copy it. Create the folder if it does not exist yet.
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Trust & safety
Security scanned
Verified clean 27 days ago
- Passed all security checks, Safe to install