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Quick Stats

Checked
marketcalls·vlatest·data

Quick Stats instantly provides key metrics from a conversation, saving time and offering immediate insights for analysis and follow-up.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add marketcalls/vectorbt-backtesting-skills --skill quick-stats -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

marketcalls

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned marketcalls/vectorbt-backtesting-skills at 05d9e8b12f.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
05d9e8b12f
Manifest
.claude/skills/quick-stats/SKILL.md
Scanned
1 file, 50 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

The quick-stats skill provides immediate numerical summaries of backtest results without generating full reports. It calculates key performance metrics like total return, annualized return, and drawdown directly from VectorBT dataframes or result objects.

When to use it

  • You need a rapid snapshot of portfolio performance before diving into detailed analysis.
  • You are iterating through multiple trading strategies and want to compare their basic stats side-by-side.
  • You require specific metrics (e.g., Sharpe ratio, max drawdown) for a dashboard or alert system without waiting for verbose output.
  • You need to validate if a backtest result meets minimum viability thresholds quickly.

Key capabilities

  • Calculates total return and annualized return automatically.
  • Determines maximum drawdown and average drawdown from equity curves.
  • Computes Sharpe ratio, Sortino ratio, and Calmar ratio based on input data.
  • Accepts VectorBT BacktestResult objects or pandas Dataframes as input.
  • Returns a concise dictionary of metrics rather than a full narrative report.

Example prompts

  • "Calculate the quick stats for this backtest result: [insert result object]"
  • "What are the total return and max drawdown for the strategy defined in this dataframe?"
  • "Give me the Sharpe ratio and annualized return for the provided VectorBT output."

Tips & gotchas

Ensure your input data is a valid BacktestResult or pandas DataFrame containing an 'equity' column; otherwise, the skill cannot compute drawdowns. This skill focuses on numerical outputs only, so it will not provide textual explanations of why performance occurred.