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 data-validationgit 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/data-validation)<a href="https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/data-validation"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/data-validation/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/data-validation"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/data-validation.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 | $0.00027 | $0.00935 |
| Opus 5 | $0.00014 | $0.00467 |
| Sonnet 5 | $0.00005 | $0.00187 |
| Haiku 4.5 | $0.00003 | $0.00093 |
Grade A, and why
data-validation-setup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cloud Data Validation Setup
One-time infrastructure setup for validating migrated data between a source database and Snowflake using the Cloud Data Validation feature via the scai CLI.
Supported sources: SQL Server, Redshift, Oracle, Teradata, PostgreSQL, Snowflake Supported target: Snowflake
Prerequisite
Load ../../data-infrastructure/SKILL.md first. It handles shared prerequisites, compute pool registration, and worker config (source host/port/credentials, source database, source schema). Return here after it completes.
For migration-source projects, validation requires target tables to already be deployed to Snowflake. For Snowflake-to-Snowflake validation, the source and target objects must already exist; do not run deployment or data migration first.
Step 1: Verify Orchestrator Service
After the shared infrastructure step has registered the compute pool, confirm the orchestrator service started:
SELECT SYSTEM$GET_SERVICE_STATUS('SNOWCONVERT_AI.DATA_MIGRATION.DATA_MIGRATION_SERVICE');
If it returns [] (suspended/not started), resume it manually:
ALTER SERVICE SNOWCONVERT_AI.DATA_MIGRATION.DATA_MIGRATION_SERVICE RESUME;
Wait 30-60s and re-check until status shows READY.
This completes infrastructure setup. The actual validation is started later by the validate-objects skill via:
progress_setup(mode="data_validation")— choose full vs incremental (+ sync strategy).validate_data(mode="setup", where=..., validation_type=..., sync_strategy=...)— generatesartifacts/data_validation/workflows/<hash>.yamland patches known toggles / sync strategy.data_infrastructure(mode="up")— bring the shared orchestrator + worker up once. Snowflake-source projects bring up only the orchestrator (start_worker=false).- Agent edits (e.g.
watermarkColumn, partition columns) thenvalidate_data(mode="run", workflow_path=...)— pure dispatch (scai data validate create-workflow) against the already-running infrastructure.
What ships with it
1 file 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.
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.
- 2d ago First seen · 77 lines · 27 tokens per session scan A 05c78feb0478
data-validation-setup is a skill published in the GitHub repository sfc-gh-dflippo/snowflake-dbt-demo (33 stars, last pushed 3d ago), licensed Apache-2.0. It adds 27 tokens to every session and 935 once invoked, about $0.0001 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 2026-09-10.
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