Agent skill

dbt-project-analyzer

Analyzes dbt projects for best practices, performance, maintainability, and generates actionable recommendations for improvement.

View SKILL.md on GitHub Repository
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Install this agent skill to your Project

npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/data-engineering-analytics/skills/dbt-project-analyzer

SKILL.md

dbt Project Analyzer

Analyzes dbt projects for best practices, performance, and maintainability following dbt Labs recommended patterns.

Overview

This skill examines dbt project structure, model dependencies, test coverage, documentation completeness, and adherence to naming conventions. It provides actionable recommendations for improving project health and maintainability.

Capabilities

  • Model dependency graph analysis - Visualize and analyze model relationships, detect circular dependencies
  • Incremental model optimization - Evaluate incremental strategies and suggest improvements
  • Materialization strategy recommendations - Recommend optimal materializations based on usage patterns
  • Test coverage analysis - Measure and report on test coverage across models
  • Documentation completeness check - Identify undocumented models, columns, and sources
  • Naming convention validation - Enforce consistent naming patterns (staging, marts, intermediate)
  • Ref/source usage validation - Detect hardcoded references and missing source definitions
  • Macro efficiency analysis - Evaluate macro usage and suggest optimizations
  • Slim CI optimization - Configure efficient CI builds with state comparison
  • Model contract validation - Verify model contracts for type safety

Input Schema

json
{
  "projectPath": {
    "type": "string",
    "description": "Path to the dbt project root directory",
    "required": true
  },
  "manifestJson": {
    "type": "object",
    "description": "Parsed manifest.json from target/ directory (optional, will be loaded if not provided)"
  },
  "catalogJson": {
    "type": "object",
    "description": "Parsed catalog.json from target/ directory (optional)"
  },
  "runResults": {
    "type": "object",
    "description": "Parsed run_results.json for performance analysis (optional)"
  },
  "analysisDepth": {
    "type": "string",
    "enum": ["quick", "standard", "deep"],
    "default": "standard",
    "description": "Depth of analysis to perform"
  },
  "focusAreas": {
    "type": "array",
    "items": {
      "type": "string",
      "enum": ["performance", "testing", "documentation", "naming", "incremental", "dependencies"]
    },
    "description": "Specific areas to focus analysis on (all if not specified)"
  }
}

Output Schema

json
{
  "healthScore": {
    "type": "number",
    "description": "Overall project health score (0-100)"
  },
  "issues": {
    "type": "array",
    "items": {
      "severity": "error|warning|info",
      "category": "string",
      "model": "string",
      "message": "string",
      "recommendation": "string",
      "line": "number"
    }
  },
  "metrics": {
    "testCoverage": {
      "type": "number",
      "description": "Percentage of models with tests"
    },
    "docCoverage": {
      "type": "number",
      "description": "Percentage of models/columns documented"
    },
    "incrementalRatio": {
      "type": "number",
      "description": "Percentage of eligible models using incremental"
    },
    "avgModelDepth": {
      "type": "number",
      "description": "Average depth in DAG"
    },
    "totalModels": {
      "type": "number"
    },
    "totalTests": {
      "type": "number"
    }
  },
  "recommendations": {
    "type": "array",
    "items": {
      "priority": "high|medium|low",
      "category": "string",
      "description": "string",
      "effort": "string",
      "impact": "string"
    }
  },
  "dependencyGraph": {
    "type": "object",
    "description": "Simplified dependency graph for visualization"
  }
}

Usage Examples

Basic Project Analysis

bash
# Invoke skill for standard analysis
/skill dbt-project-analyzer --projectPath ./my-dbt-project

Deep Analysis with Focus Areas

json
{
  "projectPath": "./analytics",
  "analysisDepth": "deep",
  "focusAreas": ["performance", "testing", "incremental"]
}

CI Integration Analysis

json
{
  "projectPath": "./dbt_project",
  "manifestJson": "./target/manifest.json",
  "runResults": "./target/run_results.json",
  "focusAreas": ["performance"]
}

Analysis Rules

Naming Conventions

Layer Pattern Example
Staging stg_<source>__<entity> stg_stripe__payments
Intermediate int_<entity>_<verb> int_payments_pivoted
Marts fct_<entity> or dim_<entity> fct_orders, dim_customers

Test Coverage Requirements

Severity Condition
Error No unique/not_null test on primary key
Warning < 50% columns have tests
Info Missing relationship tests

Materialization Guidelines

Model Type Recommended Reason
Staging View or Ephemeral Source transformations, low compute
Intermediate Ephemeral Reduce warehouse clutter
Marts Table or Incremental End-user queries, performance
Large tables (>1M rows) Incremental Reduce build time

Integration Points

MCP Server Integration

This skill integrates with the official dbt MCP server for enhanced capabilities:

  • dbt-labs/dbt-mcp - Project metadata discovery, model information, semantic layer querying
  • dbt Remote MCP Server - Cloud-hosted dbt MCP with secure endpoint access

Applicable Processes

  • dbt Project Setup (dbt-project-setup.js)
  • dbt Model Development (dbt-model-development.js)
  • Metrics Layer (metrics-layer.js)
  • Incremental Model Setup (incremental-model.js)

References

Version History

  • 1.0.0 - Initial release with core analysis capabilities

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