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Data Integrity Auditor

Checked
patricio0312rev·vlatest·data·MIT

Automatically identifies inconsistencies, errors, and anomalies within datasets to ensure data accuracy and reliability.

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 patricio0312rev/skills --skill data-integrity-auditor -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

patricio0312rev

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 patricio0312rev/skills at 79ea6af485.

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

Commit
79ea6af485
Manifest
db-management/data-integrity-auditor/SKILL.md
Scanned
1 file, 488 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 data-integrity-auditor skill enables AI agents to verify the accuracy, consistency, and reliability of information within datasets or knowledge bases. It acts as a specialized validator to ensure that processed data meets defined standards before further analysis or deployment.

When to use it

  • Validating output from other AI agents before finalizing reports or decisions.
  • Checking for hallucinations or inconsistencies in generated text against source documents.
  • Ensuring database records match expected formats and logical constraints after bulk updates.
  • Auditing knowledge base entries for factual accuracy prior to public release.

Key capabilities

  • Detects discrepancies between raw data and processed results.
  • Validates consistency across multiple data points or sources.
  • Identifies potential integrity issues in structured datasets.

Example prompts

  • "Run an integrity audit on the sales report generated earlier to check for any numerical inconsistencies."
  • "Verify that the customer contact information in this list matches the official database records."
  • "Audit the research summary for factual accuracy against the provided source articles."

Tips & gotchas

This skill requires access to the original data sources or ground truth documents to perform effective comparisons. It is most effective when used as a final step in a workflow to catch errors before they propagate downstream.