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-migrationgit 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-migration)<a href="https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/dbt-migration"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/dbt-migration/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-migration"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/dbt-migration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00056 | $0.04298 |
| Opus 5 | $0.00028 | $0.02149 |
| Sonnet 5 | $0.00011 | $0.00860 |
| Haiku 4.5 | $0.00006 | $0.00430 |
Grade A, and why
dbt-migration 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 426 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Database to dbt Migration Workflow
Purpose and When to Use
Guide AI agents through the complete migration lifecycle from Snowflake or legacy database systems (SQL Server, Oracle, Teradata, etc.) to production-quality dbt projects on Snowflake. This skill defines a structured, repeatable process while delegating platform-specific syntax translation to dedicated source-specific skills.
Activate this skill when users ask about:
- Planning a database migration to dbt
- Organizing legacy scripts for migration
- Converting views and stored procedures to dbt models
- Testing migration results against source systems
- Deploying migrated dbt projects to production
Snowflake Migration Tools
Required Two-Step Approach
- Convert to Snowflake first: Use SnowConvert AI and AI Powered Code Conversion to convert source database objects (from SQL Server, Oracle, Teradata, etc.) to Snowflake tables, views, and stored procedures.
- Then convert to dbt: Use the $dbt-migration-snowflake skill to migrate Snowflake objects to dbt models.
SnowConvert AI (Required for Supported Platforms)
IMPORTANT: For all supported platforms listed below, SnowConvert AI is a hard requirement — do not attempt manual conversion. SnowConvert AI handles edge cases, platform-specific idioms, and dependency resolution that manual translation consistently misses.
SnowConvert AI converts source DDL, views, stored procedures, functions, and additional objects (triggers, sequences, indexes) to Snowflake-compatible SQL. Download SnowConvert AI
Supported Platforms
- Full support (tables, views, procedures, functions): SQL Server, Oracle, Teradata, Redshift, Azure Synapse, IBM DB2
- Partial support (tables, views only): Sybase IQ, BigQuery, PostgreSQL, Spark SQL/Databricks, Hive, Vertica, Greenplum/Netezza
What ships with it
20 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- README.md 21 KB
- resources/ai-code-conversion.md 2.1 KB
- resources/data-migration.md 3.0 KB
- resources/data-validation-cli.md 2.4 KB
- resources/data-validation.md 3.1 KB
- resources/etl-replatform.md 3.4 KB
- resources/migration-assistant.md 2.0 KB
- resources/power-bi-repointing.md 3.1 KB
- scripts/clean_migration_docs.py 6.2 KB runs code
- scripts/clean_skill_descriptions.py 11 KB runs code
- scripts/copy_migration_docs.py 3.1 KB runs code
- scripts/fix_broken_links.py 5.8 KB runs code
- scripts/fix_markdown_lint.py 12 KB runs code
- scripts/generate_reference_index.py 4.8 KB runs code
- scripts/migrate_references.py 8.0 KB runs code
- scripts/update_skill_indexes.py 5.2 KB runs code
- translation-references/general/built-in-functions.md 322 B
- translation-references/general/README.md 508 B
- translation-references/general/subqueries.md 8.8 KB
- translation-references/README.md 2.3 KB
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.
- 11d ago First seen · 426 lines · 56 tokens per session scan A 3f4a6e77405f
dbt-migration is a skill published in the GitHub repository sfc-gh-dflippo/snowflake-dbt-demo (33 stars, last pushed 2d ago), licensed Apache-2.0. It adds 56 tokens to every session and 4,298 once invoked, about $0.0003 per session on Opus 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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