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Quality Checks

Checked
proompteng·vlatest·testing·MIT

This skill automatically reviews generated content for factual accuracy, grammar, and style, ensuring higher-quality outputs and saving you time.

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 proompteng/lab --skill quality-checks -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

proompteng

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 proompteng/lab at 6a37928f5a.

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

Commit
6a37928f5a
Manifest
skills/quality-checks/SKILL.md
Scanned
4 files, 99 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

quality-checks

What it does

This skill enables AI agents to perform automated validation and verification tasks on generated outputs, data entries, or code snippets. It ensures consistency and accuracy by comparing results against predefined rules, schemas, or reference datasets before final submission.

When to use it

  • Automated testing: Run regression tests on software builds or API responses immediately after generation.
  • Data integrity: Validate user-submitted forms or imported CSV files against strict business logic constraints.
  • Content moderation: Check generated articles or social media posts for policy violations, hallucinations, or formatting errors.
  • Code review: Automatically lint and test code snippets before merging them into a repository.

Key capabilities

  • Executes predefined validation rules and schemas on arbitrary inputs.
  • Compares output against golden datasets to detect drift or anomalies.
  • Generates detailed error reports highlighting specific failures in the checked content.
  • Supports both synchronous checks (blocking) and asynchronous batch processing.

Example prompts

  • "Run a quality check on this JSON response to ensure all required fields match our schema."
  • "Validate the generated SQL query against our security rules before execution."
  • "Check this article for factual consistency with the provided source documents."

Tips & gotchas

Ensure your validation rules are up-to-date, as outdated schemas may cause false positives on legitimate new data. For large-scale operations, configure asynchronous processing to avoid latency bottlenecks during peak usage.