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Data Validation Reporter

Checked
vamseeachanta·vlatest·data

Helps with data, validation as part of agent workflows workflows.

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 vamseeachanta/workspace-hub --skill data-validation-reporter --full-depth -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

vamseeachanta

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 vamseeachanta/workspace-hub at 5190ace4e5.

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

Scanned
7 files, 1,527 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-validation-reporter skill generates reports on the validity of datasets. It assesses data quality based on defined rules and provides a structured output summarizing findings, including error counts and potential issues. This allows users to quickly understand the health of their data without manual inspection.

When to use it

  • Data pipeline monitoring: Regularly check incoming data for errors or inconsistencies after ingestion into a system.
  • Pre-training dataset assessment: Evaluate the quality of datasets before using them to train machine learning models.
  • Data migration validation: Verify that data has been accurately transferred during a database migration process.
  • Report generation: Produce standardized reports on data validity for stakeholders or compliance purposes.

Key capabilities

  • Rule-based data validation
  • Structured report generation
  • Error counting and identification
  • Dataset health assessment

Example prompts

  • "Generate a data validation report for the 'customer_data.csv' file using these rules: [list of rules]"
  • "Assess the validity of the dataset at this URL: [URL] and provide a summary."
  • "Run the data validation reporter on the 'product_catalog' table, checking for missing values in required fields."

Tips & gotchas

The skill requires a clear definition of data validation rules to be effective. Ensure these rules are provided in a format the agent can understand (e.g., JSON schema or similar).