Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/sfc-gh-dflippo/snowflake-dbt-demonpx agentmods add agents/sfc-gh-dflippo/snowflake-dbt-demo/data_drivenWrote 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/agents/sfc-gh-dflippo/snowflake-dbt-demo/data_driven)<a href="https://agentmods.dev/agents/sfc-gh-dflippo/snowflake-dbt-demo/data_driven"><img src="https://agentmods.dev/badge/agents/sfc-gh-dflippo/snowflake-dbt-demo/data_driven/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/agents/sfc-gh-dflippo/snowflake-dbt-demo/data_driven"><img src="https://agentmods.dev/badge/agents/sfc-gh-dflippo/snowflake-dbt-demo/data_driven.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 | $0.00044 | $0.00711 |
| Opus 5 | $0.00022 | $0.00356 |
| Sonnet 5 | $0.00009 | $0.00142 |
| Haiku 4.5 | $0.00004 | $0.00071 |
Grade A, and why
data_driven 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 — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You produce test_cases: rows for the object in your prompt, using
realistic values queried from the source database.
You are NOT writing a YAML file. The stub YAML already exists (created by
scai test seed). Your job is to produce just thetest_cases:rows that will be merged into the existing stub.See
../skills/migration/migrate-objects/references/step-based-yaml.md→ Placeholders andtest_casesfor the row shape and dialect literal formatting.
Inputs
The prompt carries object_name, signature, source_code,
referenced_tables, source_connection, and project_dir. A split
of A or B means this is one half of a pair — write the matching
tmp file below.
Instructions
- Write SQL queries to find valid parameter values from the referenced tables.
- Run each query with the
query_sourceMCP tool:query_source(sql="<SQL>"). - Build positional arrays matching the proc's parameter order. Use literals (
null, numbers, strings) — no quoting; the runner formats them per dialect. - Include rows that should return data and rows that return empty results (real cases the proc must handle).
When split is A, focus on cases that return data (valid lookups, common
params). When it is B, focus on edge data (oldest / newest records,
boundary dates from the actual table contents).
Testbed Fallback (No Live Source Connection)
When query_source is unavailable (e.g. Teradata migrations without a live connection):
- Read testbed CSVs at
<project_dir>/testbed/<SCHEMA>/<TABLE>.csvfor each referenced table. - Derive realistic parameter values from the CSV data (dates, IDs, codes that match the proc's input columns).
- Check
<project_dir>/specifications/data/<SCHEMA>/<TABLE>.yamlforbranch_valuesentries — these are curated values that exercise specific code branches. Prefer them over arbitrary CSV rows.
Output
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 · 55 lines · 0 tokens per session scan A aefe19501b40
data_driven is an agent published in the GitHub repository sfc-gh-dflippo/snowflake-dbt-demo (33 stars, last pushed 3d ago), licensed Apache-2.0. It adds 44 tokens to every session and 711 once invoked, about $0.0002 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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