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Lint Check

Checked
mehdic·vlatest·other·MIT

This "Lint Check" skill analyzes your code for style and potential errors, boosting readability and preventing bugs early on.

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 mehdic/bazinga --skill lint-check -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

mehdic

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 mehdic/bazinga at 7aa4bb0f20.

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

Commit
7aa4bb0f20
Manifest
.claude/skills/lint-check/SKILL.md
Scanned
3 files, 687 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, lint-check, performs static analysis and code style checks on text files. It identifies potential errors, stylistic inconsistencies, and adherence to coding standards within the provided code or configuration files. The results are presented as a report highlighting issues that need attention.

When to use it

  • Code Review: Before submitting code changes for review, run lint-check to catch common errors early on.
  • Configuration File Validation: Ensure your YAML, JSON, or other configuration files adhere to expected formatting and syntax.
  • Automated Pipelines: Integrate lint-check into CI/CD pipelines to enforce consistent coding standards across a project.
  • Educational Purposes: Use it to learn about best practices and common pitfalls in code style.

Key capabilities

  • Static analysis of text files
  • Code style checks
  • Error identification
  • Report generation

Example prompts

  • "Run lint-check on this Python script: [script content]"
  • "Check the formatting of this YAML file: [YAML content]"
  • "Perform a code style analysis on this configuration file."

Tips & gotchas

The skill requires access to the text files you want to analyze. Ensure the AI agent has appropriate permissions and context to locate and process these files correctly.