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 vaquarkhan/data-engineering-agent-skills --skill warehouse-performance-and-cost-optimizationgit clone --depth 1 https://github.com/vaquarkhan/data-engineering-agent-skillsWrote 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/vaquarkhan/data-engineering-agent-skills/warehouse-performance-and-cost-optimization)<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/warehouse-performance-and-cost-optimization"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/warehouse-performance-and-cost-optimization/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/vaquarkhan/data-engineering-agent-skills/warehouse-performance-and-cost-optimization"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/warehouse-performance-and-cost-optimization.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 | $0.00047 | $0.00461 |
| Opus 5 | $0.00023 | $0.00230 |
| Sonnet 5 | $0.00009 | $0.00092 |
| Haiku 4.5 | $0.00005 | $0.00046 |
Grade A, and why
warehouse-performance-and-cost-optimization 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 9d 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.
What it actually says
Warehouse Performance And Cost Optimization
Overview
Use this skill when data is correct but too slow or too expensive. It helps agents treat performance and cost as measurable design concerns rather than guesswork.
When to Use
- slow warehouse queries
- runaway compute or scan cost
- poor partitioning or clustering choices
- overloaded workloads competing on shared compute
- repeated complaints about expensive marts or dashboards
Do not optimize blindly. Start from observed cost or performance signals.
Workflow
-
Identify the real bottleneck. Measure:
- scan volume
- slot or warehouse usage
- partition pruning
- join behavior
- concurrency patterns
-
Classify the problem. Common buckets:
- physical design
- SQL pattern
- workload isolation
- storage layout
- refresh frequency
-
Fix the cheapest high-impact issue first. Examples:
- partitioning
- clustering
- pre-aggregation
- materialization change
- compute right-sizing
-
Keep business correctness stable while optimizing.
-
Record the trade-off. Faster is not always cheaper, and cheaper is not always acceptable.
Common Rationalizations
| Rationalization | Reality |
|---|---|
| "We just need a bigger warehouse." | More compute often hides poor layout or query design. |
| "Optimization can wait until later." | Cost debt compounds quickly in shared platforms. |
| "The query only runs once a day." | Expensive daily jobs can still be major recurring waste. |
Red Flags
- performance work starts with no baseline measurement
- cost issues are blamed on the platform alone
- optimizations change business logic without validation
- the same expensive pattern repeats across many models
Verification
- Baseline cost or performance metrics exist
- The bottleneck category is identified
- The change preserves correctness while improving performance or cost
- The resulting trade-off is documented
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.
- 9d ago First seen · 74 lines · 47 tokens per session scan A 96a5e7f42eda
warehouse-performance-and-cost-optimization is a skill published in the GitHub repository vaquarkhan/data-engineering-agent-skills (45 stars, last pushed 3mo ago), licensed MIT. It adds 47 tokens to every session and 461 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 2026-09-03.
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