Inline backtest runner for Indian equities with EMA crossover strategy and benchmark comparison.
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add marketcalls/vectorbt-backtesting-skills --skill quick-statsCompatible with
Supported agents
Fetches OHLC data from OpenAlgo (with yfinance fallback) and runs a TA-Lib EMA 10/20 crossover strategy without file creation
Applies Indian delivery fees (0.111% + Rs 20 per order) and automatically fetches NIFTY benchmark for alpha calculation
Prints compact results summary including total return, Sharpe/Sortino ratios, max drawdown, win rate, and profit factor with plain-language metri
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionquick-statsExecute the skills CLI command in your project's root directory to begin installation:
epx add marketcalls/vectorbt-backtesting-skills --skill quick-statsFetches quick-stats from marketcalls/vectorbt-backtesting-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/quick-stats
Restart Cursor to activate quick-stats. Access via /quick-statsin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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Solid pick for teams standardizing on skills: quick-stats is focused, and the summary matches what you get after install.
I recommend quick-stats for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
We added quick-stats from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
quick-stats reduced setup friction for our internal harness; good balance of opinion and flexibility.
quick-stats is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
quick-stats fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
I recommend quick-stats for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: quick-stats is focused, and the summary matches what you get after install.
Useful defaults in quick-stats — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for quick-stats matched our evaluation — installs cleanly and behaves as described in the markdown.
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