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 dbt-performancegit 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/dbt-performance)<a href="https://agentmods.dev/skills/sfc-gh-dflippo/snowflake-dbt-demo/dbt-performance"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/dbt-performance/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/dbt-performance"><img src="https://agentmods.dev/badge/skills/sfc-gh-dflippo/snowflake-dbt-demo/dbt-performance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00052 | $0.03796 |
| Opus 5 | $0.00026 | $0.01898 |
| Sonnet 5 | $0.00010 | $0.00759 |
| Haiku 4.5 | $0.00005 | $0.00380 |
Grade A, and why
dbt-performance 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 12d 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 — 623 lines — stays where its author put it; the contents beside it link to each section on GitHub.
dbt Performance Optimization
Purpose
Transform AI agents into experts on dbt and Snowflake performance optimization, providing guidance on choosing optimal materializations, leveraging Snowflake-specific features, and implementing query optimization patterns for production-grade performance.
When to Use This Skill
Activate this skill when users ask about:
- Optimizing slow dbt model builds
- Choosing appropriate materializations for performance
- Implementing Snowflake clustering keys
- Sizing warehouses appropriately
- Converting models to incremental for performance
- Optimizing query patterns and SQL
- Troubleshooting performance bottlenecks
- Using Snowflake performance features (Gen2, query acceleration, search optimization)
Official Snowflake Documentation: Query Performance
Materialization Performance
Choose the Right Materialization
| Materialization | Build Time | Query Time | Best For |
|---|---|---|---|
| ephemeral | Fast | Varies | Staging, reusable logic |
| view | Instant | Slow | Always-fresh simple transforms |
| table | Slow | Fast | Dimensions, complex logic |
| incremental | Fast | Fast | Large facts (millions+ rows) |
Guidelines:
- Use
ephemeralfor staging (fast, no storage) - Use
tablefor dimensions - Use
incrementalfor large facts
When to Change Materializations
Change Ephemeral/View to Table When
1. Memory Constraints
Queries failing or running slowly due to memory limitations:
-- Change from ephemeral to table
{{ config(materialized='table') }}
2. CTE Reuse
Same intermediate model referenced multiple times downstream:
-- If int_customers__metrics is used by 3+ downstream models
{{ config(materialized='table') }} -- Materialize to avoid re-computation
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.
- 12d ago First seen · 623 lines · 52 tokens per session scan A cc4be6e18ef1
dbt-performance is a skill published in the GitHub repository sfc-gh-dflippo/snowflake-dbt-demo (33 stars, last pushed 2d ago), licensed Apache-2.0. It adds 52 tokens to every session and 3,796 once invoked, about $0.0003 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 2026-08-30.
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