MCPInstall

strategy-compare

Compare multiple strategies or directions (long vs short vs both) on the same symbol. Generates side-by-side stats table.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/marketcalls/vectorbt-backtesting-skills --skill strategy-compare
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads strategy-compare automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Create a strategy comparison script.

Arguments

Parse $ARGUMENTS as: symbol followed by strategy names

  • $0 = symbol (e.g., SBIN, RELIANCE, NIFTY)
  • Remaining args = strategies to compare (e.g., ema-crossover rsi donchian)

If only a symbol is given with no strategies, compare: ema-crossover, rsi, donchian, supertrend. If "long-vs-short" is one of the strategies, compare longonly vs shortonly vs both for the first real strategy.

Instructions

  1. Read the vectorbt-expert skill rules for reference patterns
  2. Create backtesting/strategy_comparison/ directory if it doesn't exist (on-demand)
  3. Create a .py file in backtesting/strategy_comparison/ named {symbol}_strategy_comparison.py
  4. The script must:
    • Fetch data once via OpenAlgo
    • If user provides a DuckDB path, load data directly via duckdb.connect(path, read_only=True). See vectorbt-expert rules/duckdb-data.md.
    • If openalgo.ta is not importable (standalone DuckDB), use inline exrem() fallback.
    • Use OpenAlgo ta for ALL indicators by default (never VectorBT built-in). Only switch to TA-Lib if the user explicitly says "talib"/"TA-Lib"
    • Always use OpenAlgo ta for specialty indicators (Supertrend, Donchian, etc.) - no TA-Lib equivalent exists
    • Clean signals with ta.exrem() (always .fillna(False) before exrem)
    • Run each strategy on the same data
    • Indian delivery fees: fees=0.00111, fixed_fees=20 for delivery equity
    • Collect key metrics from each into a side-by-side DataFrame
    • Include NIFTY benchmark in the comparison table (via OpenAlgo NSE_INDEX)
    • Print Strategy vs Benchmark comparison table: Total Return, Sharpe, Sortino, Max DD, Win Rate, Trades, Profit Factor
    • Explain results in plain language - which strategy performed best and why
    • Plot overlaid equity curves for all strategies using Plotly (template="plotly_dark")
    • Save comparison to CSV
  5. Never use icons/emojis in code or logger output

Example Usage

/strategy-compare RELIANCE ema-crossover rsi donchian /strategy-compare SBIN long-vs-short ema-crossover

FAQ

What does the strategy-compare skill do?

Compare multiple strategies or directions (long vs short vs both) on the same symbol. Generates side-by-side stats table.

How do I install strategy-compare?

Run npx skills add https://github.com/marketcalls/vectorbt-backtesting-skills --skill strategy-compare in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/strategy-compare/ (personal) or .claude/skills/strategy-compare/ (project).

Which AI agents can use strategy-compare?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is strategy-compare safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains strategy-compare?

It is published by marketcalls in marketcalls/vectorbt-backtesting-skills. It has 2,262 recorded installs.

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