rest-api-pipeline
claudeBuild dlt pipelines for REST APIs: find a source, scaffold the pipeline, add endpoints and incremental loading, debug it, validate the data and view it in a report. Requires dlt[hub].
8 skills · 1 MCP server
65
claude
quick-start
A guided path from ingestion to visualization, transformation and deployment in 3-5 prompts. Requires dlt[hub].
65 on GitHubby ScaleVector GmbHv0.1.2https://github.com/dlt-hub/dlthub-ai-harness/blob/master/LICupdated yesterdaydata
/
Plugin quick-start from marketplace dlthub-ai-harness in dlt-hub/dlthub-ai-harness. Commands read from the repo's manifest — yesterday.
What it installs
Skills (1)
quick-startThe guided entry point for dltHub AI Harness use cases — ingestion from APIs, data exploration, transformations, deployment, data quality. Use when the user names a use case or wants to be oriented before starting: 'I want to ingest from Stripe', 'show me how to go from data to dashboard', 'take me
Slash commands (1)
/quick-start:startRun the quick-start guided workflow
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claudeTurn raw dlt pipeline data into a Canonical Data Model: annotate sources, build an ontology, design a Kimball-style model and write @dlt.hub.transformation functions. Requires dlt[hub].
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init
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data-quality
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dlthub-platform
claudePrepare and deploy your dlthub workspace and pipelines to the dltHub platform, and debug failed deployments. Requires dlt[hub].
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