What is define-data-quality-checks?

A tool for turning schema hints or business rules into data-quality checks and metrics for a particular dlt pipeline or table. Checks are rules used to find invalid data; metrics are measurements of data quality.

Use it to decide and define column-level checks and load metrics for pipeline tables.

It helps translate plain requirements into concrete validation rules without running those rules immediately.

define-data-quality-checks — Skill for Claude Code by dlt-hub

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 dlt-hub/dlthub-ai-harness --skill define-data-quality-checks

Clone the repo

git clone --depth 1 https://github.com/dlt-hub/dlthub-ai-harness

Made for: Claude Code.

Or install data-quality, the plugin that ships this one along with the rest of its 4 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/dlt-hub/dlthub-ai-harness/define-data-quality-checks/github.svg)](https://agentmods.dev/skills/dlt-hub/dlthub-ai-harness/define-data-quality-checks)

Your own site

<a href="https://agentmods.dev/skills/dlt-hub/dlthub-ai-harness/define-data-quality-checks"><img src="https://agentmods.dev/badge/skills/dlt-hub/dlthub-ai-harness/define-data-quality-checks/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/dlt-hub/dlthub-ai-harness/define-data-quality-checks"><img src="https://agentmods.dev/badge/skills/dlt-hub/dlthub-ai-harness/define-data-quality-checks.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 85 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,856 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.

Model	Per session	Once invoked
Fable 5.1	$0.00085	$0.02856
Opus 5.5	$0.00034	$0.01142
Sonnet 5.5	$0.00017	$0.00571
Haiku 4.5	$0.00009	$0.00286

Measured 1mo ago against content hash 837ae536527e, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

define-data-quality-checks 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 1mo 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.

workbench/data-quality/skills/define-data-quality-checks/SKILL.md · 285 lines

The source is not reproduced here

A licence we could not identify

The repository carries a LICENSE file, but it is custom or dual enough that GitHub cannot name it and neither can this catalogue. Unknown terms are not permission, so the body is not copied here. Read the licence at the source and decide for yourself.

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.

1mo ago Changed 837ae536527e
2mo ago First seen · 285 lines · 85 tokens per session scan A 94565047d120

Subscribe to this mod's changes

define-data-quality-checks is a skill published in the GitHub repository dlt-hub/dlthub-ai-harness (65 stars, last pushed yesterday), with no licence file. It adds 85 tokens to every session and 2,856 once invoked, about $0.0003 per session on Opus 5.5. 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 2026-08-30.

Analytics and metrics

define-data-quality-checks next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
define-data-quality-checksdlt-hub/dlthub-ai-harness	Skill	65	yesterday	none	A	85	Claude Code
imagegenopenai/codex	Skill	133k	yesterday	Apache-2.0	A	113	Codex
playwright-climicrosoft/playwright	Skill	99k	yesterday	Apache-2.0	A	19	Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	4d ago	MIT	A	200	Claude Code, Codex
systematic-debuggingobra/superpowers	Skill	313k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	95	Claude Code
next-partial-prefetching-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	103	Claude Code