data-quality

data-quality is a skill for Claude Code from Methasit-Pun/data_engineer_claude_skills. It costs 126 tokens per session (1,841 once invoked), scanned A, original, no licence file.

A set of methods for checking whether data is complete, correctly formatted, within expected limits, linked properly, and behaving normally. It covers checks for tools such as Great Expectations and dbt, which help test data pipelines.

In plain words
What is it for?
Use it to define validation rules, test pipeline outputs, detect unusual values, and monitor data quality over time. It also helps check missing values, data types, ranges, and links between records.
Why use it?
It helps find bad or changing data before it causes errors in reports, applications, or production systems. It also gives teams repeatable checks and monitoring patterns instead of relying on manual inspection.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the data-engineer-skills plugin — 28 skills shipped together

Good fit Use it to define validation rules, test pipeline outputs, detect unusual values, and monitor data quality over time. It also helps check missing values, data types, ranges, and links between records.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/methasit-pun/data_engineer_claude_skills/data-quality
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Methasit-Pun/data_engineer_claude_skills --skill data-quality
Clone the repo
git clone --depth 1 https://github.com/Methasit-Pun/data_engineer_claude_skills

Made for: Claude Code.

Or install data-engineer-skills, the plugin that ships this one along with the rest of its 28 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for data-quality

README.md
[![agentmods](https://agentmods.dev/badge/skills/methasit-pun/data_engineer_claude_skills/data-quality.svg)](https://agentmods.dev/skills/methasit-pun/data_engineer_claude_skills/data-quality)
Your own site
<a href="https://agentmods.dev/skills/methasit-pun/data_engineer_claude_skills/data-quality"><img src="https://agentmods.dev/badge/skills/methasit-pun/data_engineer_claude_skills/data-quality.svg" alt="Measured on agentmods" height="20"></a>
Per session 126 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,841 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00126 $0.01841
Opus 5 $0.00063 $0.00920
Sonnet 5 $0.00025 $0.00368
Haiku 4.5 $0.00013 $0.00184

Measured 8d ago against content hash 18551749368e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

data-quality scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

06-reliability/data-quality/SKILL.md · 237 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 237 lines · 126 tokens per session scan A 18551749368e

Subscribe to this mod's changes

data-quality is a skill published in the GitHub repository Methasit-Pun/data_engineer_claude_skills (1 stars, last pushed 1mo ago), with no licence file. It adds 126 tokens to every session and 1,841 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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