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.
npx skills add sfc-gh-dflippo/snowflake-dbt-demo --skill dbt-testinggit clone --depth 1 https://github.com/sfc-gh-dflippo/snowflake-dbt-demoWrote 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.
[](https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/dbt-testing)<a href="https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/dbt-testing"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/dbt-testing/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.
<a href="https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/dbt-testing"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/dbt-testing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00057 | $0.03734 |
| Opus 5 | $0.00028 | $0.01867 |
| Sonnet 5 | $0.00011 | $0.00747 |
| Haiku 4.5 | $0.00006 | $0.00373 |
Grade A, and why
dbt-testing 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 10d 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.
This is a copy
95% identical to dbt-testing — 18 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 706 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dbt Testing
Purpose
Transform AI agents into experts on dbt testing strategies, providing guidance on implementing comprehensive data quality checks with database-enforced constraints, generic tests, and custom singular tests to ensure data integrity across all layers.
When to Use This Skill
Activate this skill when users ask about:
- Implementing data quality tests
- Adding primary key and foreign key constraints
- Using dbt_constraints package for database-level enforcement
- Creating generic (reusable) tests
- Writing singular (one-off) tests
- Testing strategies by layer (bronze/silver/gold)
- Debugging test failures
- Configuring test severity levels
- Storing test failures for analysis
Official dbt Documentation: Testing
Testing Philosophy
Implement tests in this order for maximum data quality:
- Primary Keys - Every dimension must have one
- Foreign Keys - All fact relationships
- Unique Keys - Business key constraints
- Business Rules - Domain-specific validations
- Data Quality - Completeness, accuracy, consistency
Why Use dbt_constraints?
The dbt_constraints package provides database-level enforcement (not just dbt tests):
✅ Database Enforcement - Creates actual constraints in the data warehouse ✅ Performance - Database-level constraints improve query optimization ✅ Data Integrity - Prevents invalid data at all access points (not just dbt) ✅ Documentation - Constraints visible in database metadata and BI tools ✅ Query Optimization - Database can use constraints for better execution plans
Standard dbt tests only validate during dbt test runs. dbt_constraints creates real
database constraints that are enforced 24/7.
Official dbt_constraints Documentation: GitHub - Snowflake-Labs/dbt_constraints
Package Installation
# packages.yml
packages:
- package: Snowflake-Labs/dbt_constraints
version: [">=0.8.0", "<1.0.0"]
- package: dbt-labs/dbt_utils
version: [">=1.0.0", "<2.0.0"]
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.
- 10d ago First seen · 706 lines · 57 tokens per session scan A 8aa81d5521d7
dbt-testing is a skill published in the GitHub repository sfc-gh-dflippo/snowflake-dbt-demo (33 stars, last pushed yesterday), licensed Apache-2.0. It adds 57 tokens to every session and 3,734 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to dbt-testing, differing in 18 lines, and is treated as a copy.
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