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 recommend-settingsgit 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/recommend-settings)<a href="https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/recommend-settings"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/recommend-settings/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/recommend-settings"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/recommend-settings.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 | $0.00082 | $0.00986 |
| Opus 5 | $0.00041 | $0.00493 |
| Sonnet 5 | $0.00016 | $0.00197 |
| Haiku 4.5 | $0.00008 | $0.00099 |
Grade A, and why
recommend-settings 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 — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Recommend Conversion Settings
Load this skill from convert (or code-conversion-only) right before running scai code convert. It inspects the input and proposes conversion settings for the user to confirm, then returns the chosen flags to the caller.
On Entry
Tell the user:
Tuning conversion settings. I'll scan your source and suggest SnowConvert options that fit what's in your code. You'll confirm before anything runs.
Workflow
Step 1: Load the settings catalog
Run:
scai code convert --list-settings --json
This returns { "sourceLanguage": "<Dialect>", "settings": [ { "longName", "shortName", "kind", "group", "helpText", "options", "default", "optional", "allowsMultiple", "min", "max", "currentValue" }, ... ] }.
sourceLanguageis the project's dialect — remember it as<DIALECT>.- Treat
settings[]as the ONLY valid options. Never propose a flag whoselongNameis not in this list. currentValue(when present) is what the project already has persisted — do not re-recommend a setting already at the value you'd suggest.
If the command fails, tell the user you couldn't load the catalog and skip recommendations (return no flags to the caller); do not block the conversion.
Step 2: Load dialect hints
Look for a hint file at ./reference/<DIALECT-lowercase>.md (e.g. ./reference/teradata.md). If it exists, read it — it maps source-code signals to settings with rationale. If it does not exist, proceed using each setting's helpText as your only guide (general reasoning, fewer/weaker recommendations).
Step 3: Sample the source
You do NOT need to read every file. To keep this cheap on large projects:
- From the hint file's signal patterns (or, without hints, from setting names/help), grep
source/for each signal, e.g.grep -rIl -e 'PERIOD(' -e '.LOGON' source/. - Open a representative sample — cap at ~20 files or ~200 KB total. Prefer files that matched signals plus a couple of the largest files.
- Tell the user how many files you sampled out of the total (honest coverage, not "analyzed everything").
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 · 73 lines · 0 tokens per session scan A 25c9fda12864
recommend-settings 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 82 tokens to every session and 986 once invoked, about $0.0004 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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