dbt-autofix: Skill for Claude Code

.claude/skills/add-integration-test/SKILL.md

add-integration-test is a skill for Claude Code from dbt-labs/dbt-autofix. It costs 23 tokens per session (1,497 once invoked), scanned A, original, Apache-2.0.

A workflow for adding an integration test to dbt-autofix, a tool that refactors dbt projects. Integration tests check the tool against a complete sample project, using golden files that describe the expected result.

In plain words
What is it for?
Use it to add a test project for a bug or feature, manually define its correct expected output, and run the test with pytest.
Why use it?
It turns the desired behavior into a repeatable test and helps prevent future regressions. TDD, or test-driven development, means writing the expected test behavior before the implementation is fixed.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

This is dbt-labs/dbt-autofix's own configuration. It tells Claude Code how to work on dbt-autofix itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything dbt-autofix configures →

Reuse

Borrowing it

Nothing to install: this file belongs to dbt-labs/dbt-autofix. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/dbt-labs/dbt-autofix/main/.claude/skills/add-integration-test/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/dbt-labs/dbt-autofix

Made for: Claude Code.

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 add-integration-test

README.md
[![agentmods](https://agentmods.dev/badge/skills/dbt-labs/dbt-autofix/add-integration-test/github.svg)](https://agentmods.dev/skills/dbt-labs/dbt-autofix/add-integration-test)
Your own site
<a href="https://agentmods.dev/skills/dbt-labs/dbt-autofix/add-integration-test"><img src="https://agentmods.dev/badge/skills/dbt-labs/dbt-autofix/add-integration-test/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 add-integration-test

Your own site · 80×15
<a href="https://agentmods.dev/skills/dbt-labs/dbt-autofix/add-integration-test"><img src="https://agentmods.dev/badge/skills/dbt-labs/dbt-autofix/add-integration-test.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 23 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,497 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00023 $0.01497
Opus 5.5 $0.00009 $0.00599
Sonnet 5.5 $0.00005 $0.00299
Haiku 4.5 $0.00002 $0.00150

Measured 2mo ago against content hash 638ef240a847, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

add-integration-test 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 2mo 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.

.claude/skills/add-integration-test/SKILL.md · 177 lines

How it starts

The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Add Integration Test

Create a new integration test for dbt-autofix. Integration tests verify that the refactor tool correctly transforms dbt projects.

Philosophy: Test-Driven Development

Integration tests document DESIRED behavior, not current behavior.

  • For bug fixes: Create a test that reproduces the bug, with expected output showing the correct behavior
  • For feature requests: Create a test that specifies what the feature should do
  • Tests should FAIL initially, then PASS once the fix/feature is implemented

This approach:

  1. Serves as a specification for the work
  2. Prevents regressions
  3. Automatically validates when the implementation is complete

Using GOLDIE_UPDATE: Run with GOLDIE_UPDATE=1 to understand current behavior, but don't blindly accept it as the expected output. Manually craft the _expected files to reflect what the behavior should be.

Arguments

  • $ARGUMENTS - The test project name (e.g., config_quoted_strings)

Running a single test:

uv run pytest "tests/integration_tests/test_full_dbt_projects.py::test_project_refactor[project_<name>]" -v

Example for a project named config_quoted_strings:

uv run pytest "tests/integration_tests/test_full_dbt_projects.py::test_project_refactor[project_config_quoted_strings]" -v

Naming guidance: Use descriptive names that explain what the test covers, not issue numbers. For example:

  • config_quoted_strings (not issue_221)
  • python_model_meta_config (not issue_220)
  • jinja_unmatched_endif

The name becomes project_<name> in the test projects directory.

Test Structure

Each integration test requires 3 artifacts in tests/integration_tests/dbt_projects/:

  1. project_<name>/ - Input dbt project (before refactor)

    • Minimum: dbt_project.yml + model files in models/
  2. project_<name>_expected/ - Expected output (after refactor)

    • Mirror of input with the DESIRED transformations applied
  3. project_<name>_expected.stdout - Expected JSON log output

    • One JSON object per line documenting refactors that SHOULD be applied

Read the full file on GitHub · 177 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. 2mo ago First seen · 177 lines · 23 tokens per session scan A 638ef240a847

Subscribe to this mod's changes

add-integration-test is a skill published in the GitHub repository dbt-labs/dbt-autofix (92 stars, last pushed today), licensed Apache-2.0. It adds 23 tokens to every session and 1,497 once invoked, about $0.0001 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.

Related

Other skills, from other repositories

verify-omnigent

Drive Omnigent the way a user does and prove a behavior with recorded evidence, using an isolated server, runner, and mock model plus a feature map of every user entry point. Load before reproducing a user-facing bug, before claiming a fix works, or when reviewing whether a change covered every surface (session vs.…

omnigent-ai/omnigent · 100 tokens

test-master

Generates test files, creates mocking strategies, analyzes code coverage, designs test architectures, and produces test plans and defect reports across functional, performance, and security testing disciplines. Use when writing unit tests, integration tests, or E2E tests; creating test strategies or automation…

Jeffallan/claude-skills · 104 tokens

eval-dataset-design

A guide to creating reliable test sets for AI agents. Each evaluation task includes the request, the simulated user's behaviour, a reset starting state, and a success check that can be independently verified.

bojieli/ai-agent-book · 138 tokens

dogfood

Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to dogfood, QA, exploratory test, find issues, bug hunt, or test this app on mobile.

callstack/agent-device · 55 tokens

cua-driver

Use Cua Driver for desktop or browser tasks that are awkward or unavailable through Bash/APIs, or when the user explicitly wants GUI interaction: app testing, visual bug reproduction, form filling, calendar entry, screenshots, and demo recording. Also covers Cua setup; not OpenAI Codex Computer Use or web research.

davidondrej/skills · 68 tokens

test-warp-ui

Guides testing Warp UI features and changes using the computer use tool. Use this skill only when computer-use testing was requested (explicit request or accepted offer) and the computeruse tool is available to the agent. Covers launching Warp and verifying UI behavior.

warpdotdev/warp · 55 tokens