Skills for building Data Vault 2 warehouses with the datavault4dbt dbt package — staging, hubs, links, satellites, and business-vault entities. Covers configuring the package, testing a raw vault, rehashing after hash-config changes, and troubleshooting common failures.
Plugin datavault4dbt from marketplace datavault4dbt-agent-skills in ScalefreeCOM/datavault4dbt-agent-skills. Commands read from the repo's manifest — 25 days ago.
auditing-skillsUse when checking this repository's skills for security or quality issues before sharing them, or remediating findings across skills.
configuring-datavault4dbtInstalls and configures the datavault4dbt package in a dbt project — packages.yml, copying the global vars into dbt_project.yml, hash and naming settings, and per-adapter setup. Use when setting up datavault4dbt, installing the package, changing hash/naming global variables, or adapting configuratio
rehashing-datavault4dbt-entitiesRecalculates hashkeys and hashdiffs across an existing raw vault with datavault4dbt's rehashing macros after a change to the hash algorithm, datatype, trimming, or case sensitivity — including the v1→v2.0.0 upgrade. Use when changing hash global variables, migrating hash logic, or upgrading datavaul
testing-a-datavault4dbt-projectAdds Data Vault 2 technical tests to a datavault4dbt project — hashkey uniqueness and not-null, link-to-hub referential integrity, and satellite key+load-date uniqueness — as dbt soft-constraint tests in YAML. Use when adding or reviewing tests for hubs, links, or satellites, or validating raw vault
troubleshooting-datavault4dbtDiagnoses common datavault4dbt failures — satellites capturing too many or too few rows, multi-source high-water-mark issues, ghost-record/datatype errors, and YAML-metadata compile errors. Use when a datavault4dbt model errors on compile or run, a satellite detects the wrong number of changes, or a
using-datavault4dbtBuilds Data Vault 2 models in dbt with the datavault4dbt package — staging, hubs, links, satellites, and business-vault entities — using the YAML-metadata macro pattern with correct hashkeys, hashdiffs, naming, and materializations. Use when creating or editing datavault4dbt models, setting up a raw
This plugin provides a specialized suite of skills for data engineers and database practitioners working on Google Cloud. It acts as an expert assistant, allowing you to use natural language prompts in your preferred coding agent to architect complex data pipelines, transform data with dbt, write Spark and BigQuery SQL notebooks, and orchestrate end-to-end workflows across GCP's data ecosystem.
37 skills
Snowflake SQL, data pipelines (Dynamic Tables, Streams+Tasks), Cortex AI functions, Snowpark Python, and dbt integration. Includes query helper script, reference guides, and troubleshooting.
1 skill
Data engineering, ML, and AI specialists - data pipelines, machine learning, LLM architecture
This plugin provides a specialized suite of skills for data engineers and database practitioners working on Google Cloud. It acts as an expert assistant, allowing you to use natural language prompts in your preferred coding agent to architect complex data pipelines, transform data with dbt, write Spark and BigQuery SQL notebooks, and orchestrate end-to-end workflows across GCP's data ecosystem.
37 skills
Agents for data engineering, machine learning, and AI development
12 agents
5 live-detection Databricks skills — cost-leak-hunter, cluster-forensics, uc-migration-pilot, streaming-guardian, bundle-medic — backed by the databricks-workspace-mcp server (npm). The v2 rebuild: real workspace detection over static docs.
5 skills · 1 MCP server · hooks
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