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kaggle

Listed
shepsci·v1.0.0·other·MIT

Unified Kaggle skill. Use when the user mentions kaggle, kaggle.com, Kaggle competitions, datasets, models, notebooks, GPUs, TPUs, badges, or anything Kaggle-related. Handles account setup, competitio

Install on your platform

Showing OpenClaw.

  1. 1

    Run this in your terminal

    terminal
    $

What we know about this skill

Publisher

shepsci

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: www.kaggle.com.

    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.

    Hosts contacted

    www.kaggle.comundeclared

    What it found (3 of 14)

    • skills/kaggle/modules/badges/scripts/phase_4_browser.py:20contacts www.kaggle.com
      "Go to https://www.kaggle.com/settings and fill in your bio, location, "
    • skills/kaggle/modules/badges/scripts/phase_4_browser.py:23contacts www.kaggle.com
      ("vampire", "Vampire", "Go to https://www.kaggle.com/settings and switch to the dark theme."),
    • skills/kaggle/modules/badges/scripts/phase_4_browser.py:47contacts www.kaggle.com
      "Go to https://www.kaggle.com/datasets/new and create a dataset from a URL "

  • 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 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 shepsci/kaggle-skill at a47bff9830.

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

Commit
a47bff9830
Manifest
skills/kaggle/SKILL.md
Scanned
60 files, 9,346 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

This skill provides access to and interaction with the Kaggle platform. It can assist users in setting up a Kaggle account, navigating Kaggle competitions, accessing datasets, and exploring notebooks. Furthermore, it supports understanding information related to Kaggle's computational resources like GPUs and TPUs, as well as badges earned on the platform.

When to use it

  • A user asks for help creating a Kaggle account or setting up their profile.
  • Someone needs assistance finding specific datasets available on Kaggle for a machine learning project.
  • The user wants to understand the requirements and scoring metrics of a particular Kaggle competition.
  • A user is looking for publicly shared notebooks demonstrating techniques applicable to Kaggle challenges.

Key capabilities

  • Account setup and profile management
  • Competition navigation and understanding
  • Dataset discovery and access
  • Notebook exploration
  • Information retrieval regarding GPUs, TPUs, and badges

Example prompts

  • "Can you help me create a Kaggle account?"
  • "I'm looking for datasets related to image classification on Kaggle."
  • "What are the rules of the 'Titanic - Machine Learning from Disaster' competition?"

Tips & gotchas

  • Requires an internet connection to access and interact with the Kaggle platform.
  • The skill’s functionality is dependent on the user having appropriate permissions within their Kaggle account for actions like dataset downloads or notebook execution.