What do I need to use Data Quality Audit?

The dataset; What it'll be used for; Source & freshness; Known issues.

Is Data Quality Audit free to use?

Yes — run it free in the browser playground (no API key needed for the sponsored trial, or bring any provider key), or install it into Claude Code, Cursor, ChatGPT and more via npx pm-claude-skills. MIT-licensed and open source.

Data Quality Audit

Q: How do I know the Data Quality Audit output is good?

The skill verifies itself against its own quality checks: Covers all six dimensions, not just missing values; Each issue comes with a concrete check to confirm it, not just a label; Severity is judged against the intended use of the data; Fix plan is prioritised by impact and says fix-vs-flag.

🔵 Stable🕐 updated 2026-06-21 🔷 SkillSpec L3 pm-data

Audit a dataset for the quality problems that silently break analysis — missingness, duplicates, outliers, type and range errors, consistency, and freshness — and produce a prioritised fix list. Use when asked to assess data quality, audit a dataset, check data before analysis, or explain why numbers look off. Produces a structured quality report across the standard dimensions, the specific issues found (with the checks to run), severity, and how to fix each.

▶ Run it free — no key needed 📝 Grade your existing draft View SKILL.md ↗

What to give it

▸The dataset — schema, a sample, or a description (what each column is, the grain)

▸What it'll be used for — the analysis/decision it feeds — focuses the audit

▸Source & freshness — where it comes from, how often it updates

▸Known issues — the user already suspects

✅ The bar it holds itself to

Every skill in this library self-verifies — these are this skill's own quality checks, straight from its definition.

✓Covers all six dimensions, not just missing values

✓Each issue comes with a concrete check to confirm it, not just a label

✓Severity is judged against the intended use of the data

✓Fix plan is prioritised by impact and says fix-vs-flag

✓Recommends guardrails to prevent recurrence

⚠️ What it refuses to do

Only checking for nulls and calling it done

"Clean your data" with no specific issues or checks

Treating all issues as equally severe regardless of the decision

Fixing data silently with no record of what was changed

Install

npx pm-claude-skills add --agent claude   # or codex · cursor · gemini · hermes
# or one-line MCP (every skill, any client):
claude mcp add pm-skills -- npx -y pm-claude-skills-mcp

Start with

Related skills

🔌 Embed this skill

Drop this on your blog, docs, or site — it renders a "Run this skill" card:

<div data-pm-skill="data-quality-audit"></div>
<script src="https://mohitagw15856.github.io/pm-claude-skills/embed.js" async></script>

💬 Discussion

Data Quality Audit is one of 599 open-source professional AI agent skills — all SkillSpec L3. Try them all in the browser · ⭐ Star on GitHub · Browse the full catalog