Dbt Model Planner — Data skill for Claude Code
Claude Code skill: Plan and build dbt models from schema requirements through structured planning with human review, schema validation, and multi-dialect SQL generation.
How to install Dbt Model Planner
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open wan-huiyan/dbt-model-planner and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
What Dbt Model Planner does
Claude Code skill: Plan and build dbt models from schema requirements through structured planning with human review, schema validation, and multi-dialect SQL generation.
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README
dbt Model Planner
[](https://github.com/wan-huiyan/dbt-model-planner/releases) [](https://claude.com/claude-code) [](LICENSE) [](https://github.com/wan-huiyan/dbt-model-planner/commits)
Jumping straight from a dashboard brief to dbt SQL skips the hard part: mapping every target field to a source table, validating it exists in production, and agreeing on the logic before writing a line of code. This skill guides you through that planning process with human review checkpoints before anything gets built.
What It Does
Takes a target schema (CSV spec, dashboard brief, or requirements doc) and guides you through 7 phases to build a validated dbt model:
- Understand Requirements — parse the spec, determine model grain
- Context Gathering — auto-read project config, mine conventions, explore source models, check with stakeholders
- Planning Document — structured CSV/Excel mapping every target field to source tables with transformation logic
- Human Review Loop — iterate with the team until all fields are confirmed
- Schema Validation — DESCRIBE production tables (3-part check: existence + population + freshness), write investigation queries
- Build the Model — CTE-structured SQL with recommended conventions and a dialect reference table
- Verify and QA — standalone verification query + self-contained QA queries
Key Features
- Complexity gate — lightweight path for simple models (<8 fields), full 7-phase path for complex ones
- Multi-dialect support — dialect reference table for Spark/Databricks, Snowflake, BigQuery, and Postgres/Redshift
- Human review checkpoints — blank "Review Feedback" column in
Related Skills
Schema Implementation
Structured data guide — JSON-LD patterns, page-type mapping, validation procedure
Worker Implement
Worker pipeline stage I — Implement. Read requirements + plan, execute edits on a feature branch, write run.lo
Worker Plan
Worker pipeline stage R2 — Plan. Read requirements.md, produce implementation_plan.md. Read-only on vault.
Onboarding Dbt
Write DBT .sql and schema.yml files for a Data Basis dataset
Development Workflow
Follow a structured development pipeline for making changes to the LLM Advisor and resource kit. Activate when
Cfn Knowledge Plan
Planning pipeline for deep NON-CODE deliverables (strategy docs, proposals, competitive analysis, board update
Related Agents
De Dbt Expert
Expert dbt developer for SQL modeling, testing, and documentation. Use for dbt model files (.sql in models/),
Data Eng Reviewer
Data-engineering expert for the code-review panel. Spawned when the diff touches SQL, dbt models or schema .ym
Dbt Specialist
Use this agent when you need to design, implement, or optimize dbt (data build tool) models and transformation
