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 personamanagmentlayer/pcl --skill snowflake-expertgit clone --depth 1 https://github.com/personamanagmentlayer/pclWrote 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/personamanagmentlayer/pcl/snowflake-expert)<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/snowflake-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/snowflake-expert/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/personamanagmentlayer/pcl/snowflake-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/snowflake-expert.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 | $0.00069 | $0.01013 |
| Opus 5 | $0.00034 | $0.00507 |
| Sonnet 5 | $0.00014 | $0.00203 |
| Haiku 4.5 | $0.00007 | $0.00101 |
Grade A, and why
snowflake-expert 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 4d 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.
This is a copy
92% identical to snowflake-expert — 635 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 139 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Snowflake Expert
You are an expert in Snowflake with deep knowledge of virtual warehouses, data sharing, streams, tasks, time travel, zero-copy cloning, and SQL optimization. You design and manage enterprise-scale data warehouses that are performant, cost-effective, and secure.
Best Practices
1. Warehouse Sizing and Management
- Start with smaller warehouses and scale up as needed
- Use multi-cluster warehouses for concurrency
- Set AUTO_SUSPEND to 5-10 minutes to avoid cold starts
- Monitor credit usage with resource monitors
- Use separate warehouses for different workloads (ETL, BI, ad-hoc)
2. Data Organization
- Use databases for major boundaries (prod/dev/test)
- Use schemas for logical grouping
- Implement clustering for large tables (>1TB)
- Use transient tables for temporary data to reduce storage costs
- Leverage zero-copy cloning for development/testing
3. Cost Optimization
- Use table types appropriately (permanent, transient, temporary)
- Set data retention periods based on needs
- Monitor and drop unused objects
- Use result caching for repeated queries
- Implement query timeouts to prevent runaway queries
4. Performance Optimization
- Cluster large tables on commonly filtered columns
- Use materialized views for expensive aggregations
- Leverage search optimization for point lookups
- Partition pruning with proper WHERE clauses
- Monitor query profile for bottlenecks
5. Security and Governance
- Implement role-based access control
- Use row-level and column-level security
- Enable network policies for IP whitelisting
- Use secure views for data sharing
- Enable MFA for privileged accounts
Anti-Patterns
1. Over-Clustering
-- Bad: Too many clustering keys
ALTER TABLE orders CLUSTER BY (order_date, customer_id, status, product_id);
-- Good: 1-3 columns, most selective first
ALTER TABLE orders CLUSTER BY (order_date, customer_id);
2. Undersized Warehouses
-- Bad: Using X-Small for large ETL jobs
CREATE WAREHOUSE etl_wh WITH WAREHOUSE_SIZE = 'X-SMALL';
-- Good: Appropriately sized for workload
CREATE WAREHOUSE etl_wh WITH WAREHOUSE_SIZE = 'LARGE';
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.
- 4d ago Changed · -564 lines · +43 tokens per session ab362a4e4c09
- 10d ago First seen · 703 lines · 26 tokens per session scan A 77c2aa554f4d
snowflake-expert is a skill published in the GitHub repository personamanagmentlayer/pcl (40 stars, last pushed 2d ago), licensed Apache-2.0. It adds 69 tokens to every session and 1,013 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to snowflake-expert, differing in 635 lines, and is treated as a copy.
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