dbt

dbt is a skill for Claude Code, Codex from G1Joshi/Agent-Skills. It costs 45 tokens per session (1,254 once invoked), scanned A, original, MIT.

A tool for transforming and documenting data inside a data warehouse using SQL. Its models are SQL queries, and references between them describe the order in which transformations depend on one another.

In plain words
What is it for?
Use it to turn raw warehouse tables into usable datasets, add checks such as uniqueness and non-empty values, document data models, and define shared business metrics.
Why use it?
It brings data-cleaning logic, checks, documentation, and dependencies into code instead of leaving them scattered across reports or manual warehouse work.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to turn raw warehouse tables into usable datasets, add checks such as uniqueness and non-empty values, document data models, and define shared business metrics.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/g1joshi/agent-skills/dbt
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add G1Joshi/Agent-Skills --skill dbt
Clone the repo
git clone --depth 1 https://github.com/G1Joshi/Agent-Skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for dbt

README.md
[![agentmods](https://agentmods.dev/badge/skills/g1joshi/agent-skills/dbt/github.svg)](https://agentmods.dev/skills/g1joshi/agent-skills/dbt)
Your own site
<a href="https://agentmods.dev/skills/g1joshi/agent-skills/dbt"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/dbt/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for dbt

Your own site · 80×15
<a href="https://agentmods.dev/skills/g1joshi/agent-skills/dbt"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/dbt.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,254 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00045 $0.01254
Opus 5.5 $0.00018 $0.00502
Sonnet 5.5 $0.00009 $0.00251
Haiku 4.5 $0.00005 $0.00125

Measured 22d ago against content hash b87236214d52, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

dbt scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 22d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/ai-ml/dbt/SKILL.md · 174 lines

How it starts

The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.

dbt (Data Build Tool)

dbt manages data transformation in the warehouse using SQL. v2.0 introduces the Fusion Engine (Rust) for performance.

When to Use

  • Analytics Engineering & Data Transformations: Transforming raw data inside modern cloud warehouses (Snowflake, BigQuery, Databricks, Redshift).
  • Modular SQL with Jinja & Version Control: Building reusable SQL models with DAG dependencies and macros.
  • Data Quality & Schema Testing: Enforcing unique, not_null, referential integrity, and custom singular tests.
  • Automated Data Documentation & Lineage: Generating interactive dependency lineage graphs directly from codebase schemas.

Quick Start

-- models/marts/fct_orders.sql
{{ config(materialized='table') }}

with orders as (
    select * from {{ ref('stg_orders') }}
),
payments as (
    select * from {{ ref('stg_payments') }}
)

select
    orders.order_id,
    orders.customer_id,
    orders.order_date,
    coalesce(payments.amount, 0) as total_amount
from orders
left join payments using (order_id)

Core Concepts

Declarative SQL Modeling with ref() & source()

Building transformation models with dependency resolution:

-- models/marts/core/fct_customer_orders.sql
{{
  config(
    materialized = 'incremental',
    unique_key = 'order_id',
    on_schema_change = 'fail'
  )
}}

with orders as (
    select * from {{ ref('stg_orders') }}
    {% if is_incremental() %}
      where order_date >= (select coalesce(max(order_date), '1970-01-01') from {{ this }})
    {% endif %}
),

customers as (
    select * from {{ ref('stg_customers') }}
)

select
    o.order_id,
    o.customer_id,
    c.full_name as customer_name,
    o.order_date,
    o.total_amount_usd
from orders o
inner join customers c on o.customer_id = c.customer_id

Schema Testing & Documentation in YAML

Enforcing column constraints and documentation:

# models/marts/core/schema.yml
version: 2

models:
  - name: fct_customer_orders
    description: "Daily customer order fact table combining staged orders and customer dimensions."
    columns:
      - name: order_id
        description: "Primary key for orders."
        tests:
          - unique
          - not_null

      - name: customer_id
        description: "Foreign key referencing staging customers."
        tests:
          - not_null
          - relationships:
              to: ref('stg_customers')
              field: customer_id

      - name: total_amount_usd
        description: "Total transaction value in USD."
        tests:
          - not_null

Read the full file on GitHub · 174 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 22d ago Changed · +5 lines b87236214d52
  2. 26d ago Changed · +124 lines · +30 tokens per session fee7c34ea24c
  3. 1mo ago First seen · 45 lines · 15 tokens per session scan A 1ebf543fdb12

Subscribe to this mod's changes

dbt is a skill published in the GitHub repository G1Joshi/Agent-Skills (15 stars, last pushed 23d ago), licensed MIT. It adds 45 tokens to every session and 1,254 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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