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dbt-Modelle und Warehouse-Relationen vergleichen, bevor die Mig…

Ermöglicht einem Agenten, dbt-Paritätsprüfungen, Relations-Diffs sowie Zeilen- oder Wertevergleiche durchzuführen, damit Refactorings und Quelltausch vor dem Rollout verifiziert werden können.

Was ist dbt-Modelle und Warehouse-Relationen vergleichen, bevor die Mig…?

Diese Fähigkeit ermöglicht es einem KI-Agenten, automatisierte Datenintegritätsprüfungen zwischen dbt-Modellen und tatsächlichen Warehouse-Relationen durchzuführen, bevor eine Migration als vertrauenswürdig eingestuft wird. Sie stützt sich auf das Paket dbt-audit-helper, das Hilfsmakros für Paritätsprüfungen, Unterschiede zwischen Relationen sowie Zeilen- oder Wertevergleiche bereitstellt. Der Agent kann so Schema- und Datenunterschiede zwischen Quell- und Zieltabellen identifizieren, bevor Änderungen ausgerollt werden. Die Fähigkeit unterstützt beliebige Warehouse-Engines, die von dbt Core unterstützt werden, und erfordert die Installation des Pakets in der packages.yml-Datei des Projekts. Besonders nützlich ist sie für Refactorings, Quelltausch oder Schemaänderungen, bei denen sichergestellt werden muss, dass die Ausgabe nach der Migration identisch zur vorherigen ist. Die Prüfungen erfolgen auf Spaltenebene und erlauben Ausschlüsse sowie die Neuanordnung der Reihenfolge.

Funktioniert mit~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/compare-dbt-models-and-warehouse-relations-before-trusting-migration-parity-with-dbt-audit-helper
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Dokumentation

dbt-Modelle und Warehouse-Relationen vergleichen, bevor die Migrationsparität mit dbt-audit-helper bestätigt wird

Ermöglicht einem Agenten, dbt-Paritätsprüfungen, Relations-Diffs sowie Zeilen- oder Wertevergleiche durchzuführen, damit Refactorings und Quelltausch vor dem Rollout verifiziert werden können.

Voraussetzungen

dbt Core, Warehouse-Zugangsdaten, dbt-audit-helper-Paket

Installation

Anforderungen und Einschränkungen aus dem Upstream:

  • Jede Relation muss dieselben Spalten mit denselben Namen haben; sie müssen jedoch nicht in derselben Reihenfolge sein.
  • Jede Relation muss dieselben Spalten mit denselben Namen haben; sie müssen jedoch nicht in derselben Reihenfolge sein. Erstellen Sie lange Listen mit wenigen Ausschlüssen mit dbt_utils.get_filtered_columns_in_relation oder übergeben Sie None und die ...
  • Jede Relation muss dieselben Spalten mit denselben Namen haben; sie müssen jedoch nicht in derselben Reihenfolge sein. Verwenden Sie exclude_columns, wenn einige Spalten nur in einer Relation existieren.

Grundlegende Nutzung oder Einstiegsnotizen:

Dokumentation

Quelle

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

Academic Paper Citation Network Mapper

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ACF Custom Fields REST Exposer

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ACF Extended for Advanced Custom Fields Workflows

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act Local GitHub Actions Runner

act is an open-source CLI tool that runs GitHub Actions workflows locally using Docker, enabling fast feedback on workflow changes without pushing to GitHub. It is a standard tool for local Actions development and testing.

Add a browser review checkpoint before risky agent actions with

Use AgentClick when an agent should pause before risky commands, plans, drafts, or code changes so a human can inspect, edit, approve, or reject them in a purpose-built browser UI.

Add Claude design-system and accessibility workflows with UX/UI

Use UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.

Add executable smoke tests for shell scripts and CLIs before ref

Use Bats-core when an agent needs to turn fragile shell scripts or command-line workflows into something it can verify repeatedly after edits. The agent writes focused Bash tests for success paths, failure paths, and output contracts, then runs them locally or in CI before a refactor, release, or incident fix goes out.

Add graph-backed memory and context retrieval to agent workflows

Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.

Add IDE-style semantic code navigation and symbol-safe refactors

Give a coding agent symbol-aware lookup, cross-file rename, and structural edit tools before it starts making brittle text-only changes.

Add managed long-term memory to LangGraph agents with LangMem

Give LangGraph agents memory management and search tools so they can store, retrieve, and update durable facts across sessions.

Add multimodal lifelong memory to MCP and Python agents with Sim

Use SimpleMem to store, compress, index, and retrieve text or multimodal memories for agents through MCP or Python integrations.

Add persistent project memory and hook-driven synthesis with Cla

Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.

Add Postgres-native vector retrieval to agent and RAG workflows

Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.

Address GitHub PR review comments from the current branch with g

Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.

Add runtime guardrails to TypeScript agents with VoltAgent

Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.

Add temporal context memory to agent workflows with Zep

Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.

Adobe Firefly API Batch Image Generator

Calls Adobe Firefly

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