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 etl-elt-and-modernization-strategygit 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/etl-elt-and-modernization-strategy)<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/etl-elt-and-modernization-strategy"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/etl-elt-and-modernization-strategy/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/etl-elt-and-modernization-strategy"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/etl-elt-and-modernization-strategy.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 | $0.00054 | $0.00702 |
| Opus 5 | $0.00027 | $0.00351 |
| Sonnet 5 | $0.00011 | $0.00140 |
| Haiku 4.5 | $0.00005 | $0.00070 |
Grade A, and why
etl-elt-and-modernization-strategy 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 — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ETL ELT And Modernization Strategy
Overview
Use this skill when the hard part is not a single job, but deciding where transformations should run and how a data estate should modernize over time. It helps agents reason about ETL versus ELT, pushdown versus external compute, orchestration boundaries, migration sequencing, and proof of parity during modernization.
When to Use
- choosing between
ETL,ELT, or hybrid transformation patterns - moving from legacy ETL tools into warehouse, dbt, Spark, or lakehouse execution
- redesigning ingestion and transformation boundaries across raw, curated, and publish layers
- reducing operational sprawl caused by duplicate transformation logic
- modernizing batch-first estates without breaking existing delivery expectations
Do not assume ELT is always better just because the warehouse is powerful.
Workflow
-
Define the transformation problem clearly. Clarify:
- source latency and volume
- data quality expectations
- transformation complexity
- cost sensitivity
- publish or consumption latency
-
Map the current execution estate. Include:
- where extraction happens
- where transformations happen today
- what logic is duplicated across tools
- where lineage or observability breaks
- what jobs are hardest to change safely
-
Choose the right execution boundary. Consider:
ETLwhen data must be reshaped or protected before landingELTwhen warehouse or lakehouse pushdown improves maintainability and scaling- hybrid patterns when extraction, privacy controls, or heavy preprocessing must happen before durable load
-
Plan the modernization path. Decide:
- what stays temporarily on the old path
- what moves first
- how parity will be measured
- how cutover and rollback will work
-
Prove the new shape operationally. Require:
- reconciliation evidence
- cost and performance review
- lineage continuity
- ownership and support readiness
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 · 81 lines · 54 tokens per session scan A 71600e1d6697
etl-elt-and-modernization-strategy is a skill published in the GitHub repository vaquarkhan/data-engineering-agent-skills (45 stars, last pushed 3mo ago), licensed MIT. It adds 54 tokens to every session and 702 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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