
strategy-compare
Compare multiple strategies or directions (long vs short vs both) on the same symbol. Generates side-by-side stats table.
- Installs
- 2.3K
- Last 24h
- —
- Trending rank
- —
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/marketcalls/vectorbt-backtesting-skills --skill strategy-compare- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads strategy-compare automatically when relevant.
- 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
- Read the vectorbt-expert skill rules for reference patterns
- Create
backtesting/strategy_comparison/directory if it doesn't exist (on-demand) - Create a
.pyfile inbacktesting/strategy_comparison/named{symbol}_strategy_comparison.py - 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-expertrules/duckdb-data.md. - If
openalgo.tais not importable (standalone DuckDB), use inlineexrem()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=20for 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
- 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.
More from marketcalls/vectorbt-backtesting-skills
backtest
marketcalls/vectorbt-backtesting-skills
Quick backtest a strategy on a symbol. Creates a complete .py script with data fetch, signals, backtest, stats, and plots.
vectorbt-expert
marketcalls/vectorbt-backtesting-skills
VectorBT backtesting expert. Use when user asks to backtest strategies, create entry/exit signals, analyze portfolio performance, optimize parameters, fetch historical data, use VectorBT/vectorbt, compare strategies, position sizing, equity curves, drawdown charts, or trade analysis. Also triggers for openalgo.ta helpers (exrem, crossover, crossunder, flip, donchian, supertrend).
optimize
marketcalls/vectorbt-backtesting-skills
Optimize strategy parameters using VectorBT. Tests parameter combinations and generates heatmaps.
quick-stats
marketcalls/vectorbt-backtesting-skills
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.
setup
marketcalls/vectorbt-backtesting-skills
Set up the Python backtesting environment. Detects OS, creates virtual environment, installs dependencies (openalgo, ta-lib, vectorbt, plotly), and creates the backtesting folder structure.
Popular other skills
hyperframes-cli
heygen-com/hyperframes
The HyperFrames CLI by job - scaffold, check, look at frames, edit the timeline, preview, render locally or in the cloud, publish, project history - plus reading its JSON and recovering from build or render failures.
triage
mattpocock/skills
Move issues and external PRs through a state machine of triage roles, categorise, verify, grill if needed, and write agent-ready briefs.
ask-matt
mattpocock/skills
Ask which skill or flow fits your situation. A router over the skills in this repo.
to-questionnaire
mattpocock/skills
Turn a decision you can't fully answer into a questionnaire for someone else to fill in.
loop-me
mattpocock/skills
Grill me about specs for the workflows I want to build, within this workspace.