dbt-transformation-patterns
Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing.
Works with
--- name: dbt-transformation-patterns description: Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing. license: MIT --- # dbt Transformation Patterns Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing. ## Use this skill when - Building data transformation pipelines with dbt - Organizing models into staging, intermediate, and marts layers - Implementing data quality tests and documentation - Creating incremental models for large datasets - Setting up dbt project structure and conventions ## Do not use this skill when - The project is not using dbt or a warehouse-backed workflow - You only need ad-hoc SQL queries - There is no access to source data or schemas ## Instructions - Define model layers, naming, and ownership. - Implement tests, documentation, and freshness checks. - Choose materializations and incremental strategies. - Optimize runs with selectors and CI workflows. - If detailed patterns are required, open `resources/implementation-playbook.md`. ## Resources - `resources/implementation-playbook.md` for detailed dbt patterns and examples. ## Limitations - Use this skill only when the task clearly matches the scope described above. - Do not treat the output as a substitute for environment-specific validation, testing, or expert review. - Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
More Testing skills
tdd
mattpocock/skills
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
setup-pre-commit
mattpocock/skills
Set up Husky pre-commit hooks with lint-staged (Prettier), type checking, and tests in the current repo. Use when user wants to add pre-commit hooks, set up Husky, configure lint-staged, or add commit-time formatting/typechecking/testing.
agent-browser
vercel-labs/agent-browser
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.

