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 migrate-sas7bdat-to-snowflakegit 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/migrate-sas7bdat-to-snowflake)<a href="https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/migrate-sas7bdat-to-snowflake"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/migrate-sas7bdat-to-snowflake/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/migrate-sas7bdat-to-snowflake"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/migrate-sas7bdat-to-snowflake.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 | $0.00115 | $0.02486 |
| Opus 5 | $0.00057 | $0.01243 |
| Sonnet 5 | $0.00023 | $0.00497 |
| Haiku 4.5 | $0.00012 | $0.00249 |
Grade A, and why
migrate-sas7bdat-to-snowflake 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 — 227 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Migrate .sas7bdat Files from Stage to Snowflake
© Snowflake Inc. This skill and its contents are the proprietary intellectual property of Snowflake Inc.
Load one or many .sas7bdat files that already sit on a Snowflake stage into tables.
All parsing and loading runs inside Snowflake (a Python stored procedure using
pandas.read_sas + SnowflakeFile). Nothing is parsed on the client.
Mental model
- The stage may contain subfolders. Each subfolder = one target table (all
.sas7bdatfiles directly inside it are appended into that table). Files at the stage root (no subfolder) = one table each. - A single engine stored procedure does all the work. A one-time load just
CALLs it once. An ongoing load wraps that same proc in a scheduled Task and uses a control table to load only new/changed files. - The proc refreshes the stage's directory table itself at the start of every run, so both one-time and scheduled loads always see newly-arrived files. (First-time setup still enables the directory table; see Step 0.)
Prerequisites
- The stage already exists and points at the
.sas7bdatfiles. (This skill verifies it; it does not create the stage.) - Role can
CREATE TABLE,CREATE PROCEDURE, and (ongoing only)CREATE TASK+EXECUTE TASKin the target schema, plusUSAGE+READon the stage. - A warehouse is available. For large files (>~500 MB) prefer a Snowpark-optimized
warehouse — see
references/architecture.md.
Setup (always do first)
Load references/architecture.md — it holds the exact server-side read pattern,
SAS date/encoding handling, memory/chunking, and warehouse guidance you will need
while deploying.
Step 0: Confirm stage and directory table
-
Ask the user for the stage name and target database/schema/warehouse.
-
Verify the stage and check whether a directory table is enabled (the engine enumerates files with
DIRECTORY(@stage), which requires one):DESCRIBE STAGE <stage>;Look at the
directoryproperty. If files sit on an external stage, also confirm a storage integration is in use.
What ships with it
6 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.
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 · 227 lines · 115 tokens per session scan A 6ee491479889
migrate-sas7bdat-to-snowflake 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 115 tokens to every session and 2,486 once invoked, about $0.0006 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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