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 searchgit 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/search)<a href="https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/search"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/search/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/search"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/search.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 | $0.00032 | $0.01457 |
| Opus 5 | $0.00016 | $0.00728 |
| Sonnet 5 | $0.00006 | $0.00291 |
| Haiku 4.5 | $0.00003 | $0.00146 |
Grade A, and why
rule-engine-search 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rule Search
Find applicable rules for a converted SQL file. All search happens in Snowflake — no local rule files. The search_rules MCP tool handles syncing file content and running queries so the SQL file content stays out of the agent's context window.
Prerequisites
- Rule engine set up (../SKILL.md)
- A converted SQL file to scan (e.g.,
snowflake/<type>/<schema>/<name>.sql)
Search for Applicable Rules
Use the search_rules tool with:
file_path=<sql_file_path>description="<brief description of the code and its migration-relevant patterns>"
Always pass description — your description of the code's structure and patterns (e.g., "procedure with dynamic SQL via sp_executesql, CONVERT with date style codes, and cursor-based iteration"). This is prepended to the structural fingerprint the tool extracts, significantly improving Cortex semantic search relevance. You've already read the code, so summarize what you see.
The tool:
- Reads the SQL file locally
- Syncs it to
RULE_ENGINE.CODE_UNITS_SQLvia MERGE (so it's available for reverse searches) - Runs regex pattern matching (
REGEXP_LIKE) — deterministic, pattern-based hits - Builds a search query from your
description+ a structural fingerprint (migration-relevant lines extracted from the procedure body) - Runs Cortex semantic search (
RULE_SEARCH!SEARCH) using that query — catches structural patterns regex might miss - Scans for EWI markers (
SSC-EWI-*,SSC-FDM-*) and resolves to local reference files - Deduplicates rules by
id(regex hits take precedence) - Returns a JSON object with
rules(sorted by priority) andewi_references
Output Format
{
"rules": [
{
"id": "isnull-to-coalesce",
"name": "Replace ISNULL with COALESCE",
"description": "...",
"replacement_mode": "regex",
"priority": 10,
"replacement_find": "ISNULL\\s*\\(",
"replacement_replace": "COALESCE(",
"ai_context": null,
"examples": [...],
"match_source": "regex"
},
{
"id": "variable-binding",
"name": "Variable binding colon prefix",
"description": "...",
"replacement_mode": "ai",
"ai_context": "...",
"match_source": "semantic"
}
],
"ewi_references": [
{
"ewi_code": "SSC-EWI-0056",
"title": "SSC-EWI-0056 - User-Defined Types Not Supported",
"reference_file": "/path/to/resolving-ewis/reference/SSC-EWI-0056.md"
}
]
}
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 · 136 lines · 32 tokens per session scan A ed3d280a50ae
rule-engine-search 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 32 tokens to every session and 1,457 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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