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X Impact Checker

Checked
manojbajaj95·vlatest·ai-ml·MIT

The X Impact Checker analyzes user prompts to gauge potential bias or harmful outputs, ensuring safer and more responsible AI interactions.

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 manojbajaj95/claude-gtm-plugin --skill x-impact-checker -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

manojbajaj95

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 manojbajaj95/gtm-skills at 0830a46f4c.

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

Commit
0830a46f4c
Manifest
skills/x-impact-checker/SKILL.md
Scanned
2 files, 540 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 manojbajaj95-x-impact-checker skill assesses the potential impact of changes or updates. It appears designed to evaluate the effects of modifications, likely within a technical context like marketing technology (gtm). The tool provides insights into how these changes might affect various aspects of a system or process.

When to use it

  • Before deploying code changes to a live environment to predict potential issues.
  • When evaluating the impact of new feature implementations on existing workflows.
  • To understand the consequences of configuration adjustments in marketing technology platforms.
  • During A/B testing to analyze the effect of different variations.

Key capabilities

  • Impact assessment
  • Change evaluation
  • Workflow analysis
  • Technical change review

Example prompts

  • "Assess the impact of updating the tracking pixel version."
  • "What are the potential consequences of modifying this GTM container?"
  • "Evaluate the effect of implementing a new data layer variable."

Tips & gotchas

This skill likely requires some familiarity with the specific system or platform being evaluated. The accuracy of the assessment depends on the quality and completeness of the information provided to the AI agent.