Quickly fetch data and print key backtest stats for a symbol with a default EMA crossover strategy. No file creation needed - runs inline in a notebook cell or prints to console.

GitHub
Install command
npx skhub add marketcalls/quick-stats
Markdown
SKILL.md

Generate a quick inline backtest and print stats. Do NOT create a file - output code directly for the user to run or execute in a notebook.

Arguments

  • $0 = symbol (e.g., SBIN, RELIANCE). Default: SBIN
  • $1 = exchange. Default: NSE
  • $2 = interval. Default: D

Instructions

Generate a single code block the user can paste into a Jupyter cell or run as a script. The code must:

  1. Fetch data from OpenAlgo (or DuckDB if user provides a DB path, or yfinance as fallback)
  2. Use OpenAlgo ta for EMA 10/20 crossover by default (never VectorBT built-in); only use TA-Lib if the user explicitly says "talib"/"TA-Lib"
  3. Clean signals with ta.exrem() (always .fillna(False) before exrem)
  4. Use Indian delivery fees: fees=0.00111, fixed_fees=20
  5. Fetch NIFTY benchmark via OpenAlgo (symbol="NIFTY", exchange="NSE_INDEX")
  6. Print a compact results summary:
Symbol: SBIN | Exchange: NSE | Interval: D
Strategy: EMA 10/20 Crossover
Period: 2023-01-01 to 2026-02-27
Fees: Delivery Equity (0.111% + Rs 20/order)
-------------------------------------------
Total Return:    45.23%
Sharpe Ratio:    1.45
Sortino Ratio:   2.01
Max Drawdown:   -12.34%
Win Rate:        42.5%
Profit Factor:   1.67
Total Trades:    28
-------------------------------------------
Benchmark (NIFTY): 32.10%
Alpha:           +13.13%
  1. Explain key metrics in plain language for normal traders
  2. Show equity curve plot using Plotly (template="plotly_dark")

Example Usage

/quick-stats RELIANCE /quick-stats HDFCBANK NSE 1h

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Version
Latest version metadata

Version

v2026.09.24

Published

Sep 24, 2026

Category

Uncategorized

License

Not specified

Source path

.claude/skills/quick-stats

Default branch

master

Latest commit

05d9e8b

Tree SHA

c84caea