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Tennis Data

Checked
machina-sports·vlatest·data·MIT

Analyzes historical tennis match data—scores, stats, player performance—to identify trends and potential outcomes.

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 machina-sports/sports-skills --skill tennis-data -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

machina-sports

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 machina-sports/sports-skills at 3be3624236.

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

Commit
3be3624236
Manifest
skills/tennis-data/SKILL.md
Scanned
6 files, 227 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

What it does

The tennis-data skill enables AI agents to access and analyze specific datasets related to tennis, facilitating informed decision-making based on match statistics or player performance metrics. It serves as a specialized data retrieval tool within the sports domain.

When to use it

  • Analyzing historical match results to predict potential outcomes for upcoming tournaments.
  • Comparing player statistics such as serve speed, win percentages, or break points saved.
  • Generating reports on team or individual performance trends over specific seasons.
  • Supporting fantasy tennis leagues with real-time or historical data insights.

Key capabilities

  • Retrieval of structured tennis-related datasets.
  • Support for statistical analysis and pattern recognition within match data.
  • Integration with AI agents to enhance sports analytics workflows.

Example prompts

  • "Retrieve the last five head-to-head matches between Novak Djokovic and Carlos Alcaraz."
  • "Analyze Rafael Nadal's serve statistics during clay court tournaments in 2023."
  • "Generate a summary of key performance indicators for the top 10 ATP players this year."

Tips & gotchas

Ensure your AI agent has proper permissions to access external sports databases if the skill relies on live feeds. This skill is best used when specific, data-driven insights are required rather than general tennis commentary.