dbt-transformation-patterns

Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.

Install with Tessl CLI

npx tessl i github:Dicklesworthstone/pi_agent_rust --skill dbt-transformation-patterns

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Review — 77%

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Validation — 10 / 11 Passed

Validation for skill structure

SKILL.md

Review

Evals

Evaluation results

99%

16%

SaaS Analytics Staging Layer Setup

Staging layer structure and source definitions

Criteria

Without context

With context

stg_ naming convention

100%

Staging directory structure

100%

Source YAML file naming

100%

Model YAML file naming

50%

100%

Source freshness config

40%

100%

Source column tests

100%

CTE pattern

100%

source() macro used

100%

Column renaming — id to entity_id

100%

Column renaming — _loaded_at

100%

Lowercase string fields

100%

83%

Cents-to-dollars conversion

100%

Model YAML documentation

100%

Without context: $0.4771 · 1m 44s · 26 turns · 22 in / 6,396 out tokens

With context: $0.8460 · 2m 32s · 33 turns · 81 in / 9,376 out tokens

90%

E-Commerce Order Processing Pipeline

Incremental model strategies and intermediate layer

Criteria

Without context

With context

int_ prefix naming

100%

fct_ prefix naming

100%

Directory structure

100%

ref() macro used

100%

Incremental materialization

100%

unique_key specified

100%

Merge strategy for updates

100%

merge_update_columns

100%

is_incremental() filter

100%

Filter uses max(updated_at)

100%

Intermediate uses CTE structure

100%

on_schema_change config

40%

Without context: $0.4498 · 1m 38s · 23 turns · 21 in / 5,927 out tokens

With context: $0.6753 · 2m 15s · 29 turns · 356 in / 8,073 out tokens

97%

12%

Customer Analytics Data Mart

Project configuration, macros, and mart dimension models

Criteria

Without context

With context

Layer materializations

66%

Schema assignments

100%

vars for start date

100%

generate_schema_name macro

100%

limit_data_in_dev macro

100%

DRY utility macro

100%

dim_ prefix naming

100%

Surrogate key

100%

_loaded_at metadata

42%

100%

ref() macro used

100%

dbt_utils tests

100%

packages.yml

100%

Model YAML documentation

100%

Without context: $0.8205 · 3m 44s · 31 turns · 31 in / 12,003 out tokens

With context: $1.1211 · 3m 59s · 34 turns · 281 in / 13,866 out tokens

Evaluated: 4 days ago
Agent: Claude Code

Table of Contents

SaaS Analytics Staging Layer Setup E-Commerce Order Processing Pipeline Customer Analytics Data Mart

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