--- title: dltHub AI Workbench data quality toolkit: schema-aware... description: dltHub's AI Workbench data quality toolkit bootstraps checks directly from dlt's existing schema metadata (primary keys, non-nullable columns, uniqueness... canonical: https://daily.dev/posts/dlthub-ai-workbench-data-quality-toolkit-schema-aware-checks-that-route-their-own-fixes-hx674ay6u twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: dltHub AI Workbench data quality toolkit: schema-aware checks that route their own fixes | daily.dev og:description: dltHub's AI Workbench data quality toolkit bootstraps checks directly from dlt's existing schema metadata (primary keys, non-nullable columns, uniqueness... og:url: https://daily.dev/posts/dlthub-ai-workbench-data-quality-toolkit-schema-aware-checks-that-route-their-own-fixes-hx674ay6u og:image: https://api.daily.dev/og/posts/HX674Ay6U.png og:image:alt: dltHub AI Workbench data quality toolkit: schema-aware checks that route their own fixes og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # dltHub AI Workbench data quality toolkit: schema-aware checks that route their own fixes **[dltHub](https://daily.dev/sources/dlthub)** · 7 min read · 1 upvotes · 0 comments ## Summary dltHub's AI Workbench data quality toolkit bootstraps checks directly from dlt's existing schema metadata (primary keys, non-nullable columns, uniqueness hints), samples columns before writing any rules, and embeds checks as decorators inside pipeline.run() via @dq.with_checks and @dq.with_metrics. Results are stored in destination tables (_dlt_checks, _dlt_dq_metrics) for querying or alerting. When failures occur, an LLM routes the fix to the appropriate toolkit: ingestion issues go to rest-api-pipeline, modeling issues to transformations, anomalies to data-exploration. This contrasts with tools like Great Expectations, which only report failures without routing fixes. The toolkit is part of dltHub Pro with a free trial available. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Building production-ready data pipelines in Microsoft Fabric: A complete data quality framework with dlthub](https://daily.dev/posts/building-production-ready-data-pipelines-in-microsoft-fabric-a-complete-data-quality-framework-with-rytf4inro) · dltHub · 0 upvotes · 0 comments - [AI Workbench: Ontology driven data modelling toolkit preview](https://daily.dev/posts/ai-workbench-ontology-driven-data-modelling-toolkit-preview-faks1csq2) · dltHub · 0 upvotes · 0 comments - [AI-augmented data quality engineering](https://daily.dev/posts/ai-augmented-data-quality-engineering-1kwdx3pnj) · InfoWorld · 2 upvotes · 0 comments - [Grab Adds Real-Time Data Quality Monitoring to Its Platform](https://daily.dev/posts/grab-adds-real-time-data-quality-monitoring-to-its-platform-8kkpu4hkw) · InfoQ · 0 upvotes · 0 comments - [Master Data Quality Checks: Essential Strategies for Data Engineers](https://daily.dev/posts/master-data-quality-checks-essential-strategies-for-data-engineers-xcdhgtz11) · Decube · 1 upvotes · 0 comments --- Tags: [#backend](https://daily.dev/tags/backend), [#ai-agents](https://daily.dev/tags/ai-agents), [#data-quality](https://daily.dev/tags/data-quality) [View this post on daily.dev](https://daily.dev/posts/dlthub-ai-workbench-data-quality-toolkit-schema-aware-checks-that-route-their-own-fixes-hx674ay6u) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"dltHub AI Workbench data quality toolkit: schema-aware checks that route their own fixes","url":"https://daily.dev/posts/dlthub-ai-workbench-data-quality-toolkit-schema-aware-checks-that-route-their-own-fixes-hx674ay6u","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/dlthub-ai-workbench-data-quality-toolkit-schema-aware-checks-that-route-their-own-fixes-hx674ay6u"},"datePublished":"2026-06-02T00:01:23.233Z","dateModified":"2026-06-02T00:01:54.062Z","description":"dltHub's AI Workbench data quality toolkit bootstraps checks directly from dlt's existing schema metadata (primary keys, non-nullable columns, uniqueness...","image":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/6d822980a364a558dec92b2b59a364a0?_a=AQAEuop","thumbnailUrl":"https://media.daily.dev/image/upload/f_auto,q_auto/v1/posts/6d822980a364a558dec92b2b59a364a0?_a=AQAEuop","isAccessibleForFree":true,"articleSection":"dltHub","inLanguage":"en","publisher":{"@type":"Organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180}},"author":{"@type":"Organization","name":"dltHub","logo":"https://media.daily.dev/image/upload/s--lanGOBQH--/f_auto/v1734606584/logos/dlthub","url":"https://daily.dev/sources/dlthub"},"commentCount":0,"discussionUrl":"https://daily.dev/posts/dlthub-ai-workbench-data-quality-toolkit-schema-aware-checks-that-route-their-own-fixes-hx674ay6u","interactionStatistic":[{"@type":"InteractionCounter","interactionType":{"@type":"LikeAction"},"userInteractionCount":1},{"@type":"InteractionCounter","interactionType":{"@type":"CommentAction"},"userInteractionCount":0}],"keywords":"backend,ai-agents,data-quality","timeRequired":"PT7M"} {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"dltHub","item":"https://daily.dev/sources/dlthub"},{"@type":"ListItem","position":3,"name":"dltHub AI Workbench data quality toolkit: schema-aware checks that route their own fixes"}]} ```