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 delta-lake-and-medallion-architecturegit 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/delta-lake-and-medallion-architecture)<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/delta-lake-and-medallion-architecture"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/delta-lake-and-medallion-architecture/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/delta-lake-and-medallion-architecture"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/delta-lake-and-medallion-architecture.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 | $0.00059 | $0.00568 |
| Opus 5 | $0.00030 | $0.00284 |
| Sonnet 5 | $0.00012 | $0.00114 |
| Haiku 4.5 | $0.00006 | $0.00057 |
Grade A, and why
delta-lake-and-medallion-architecture 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Delta Lake And Medallion Architecture
Overview
Use this skill when a Delta Lake-based lakehouse needs more than generic table-format guidance. It helps agents design medallion-style layers, transactional update behavior, CDC merges, and publish-safe transformation paths for Delta-centric platforms.
When to Use
- designing
bronze,silver, andgoldlayering - implementing
Delta Lakemerges, upserts, or deletes - building
Databricks-centered batch and streaming lakehouse flows - deciding how raw landing data evolves into trusted publish outputs
Do not use medallion terminology as decoration if the layers do not carry distinct responsibilities.
Workflow
-
Define the layer responsibilities. Typical pattern:
- bronze: raw or lightly standardized landing
- silver: cleaned, conformed, contract-aware transformations
- gold: business-facing publish-ready outputs
-
Define movement rules between layers. Capture:
- validation requirements
- mutation behavior
- CDC merge strategy
- schema enforcement and evolution policy
-
Keep bronze permissive and gold disciplined. Raw survival and publish trust need different operating rules.
-
Coordinate batch and streaming writers carefully. Checkpoints, merges, and small-file behavior must support recovery and maintenance.
-
Plan maintenance as part of the architecture. Include:
- compaction
- retention
- optimization
- cleanup
Common Rationalizations
| Rationalization | Reality |
|---|---|
| "Bronze, silver, and gold are enough architecture by themselves." | Layer names without contracts and rules create confusion, not design clarity. |
| "We can merge everything directly into gold." | Business-facing layers need stronger validation and stability than raw ingestion paths. |
| "Delta transactions solve every operational problem." | You still need thoughtful layering, maintenance, and replay design. |
Red Flags
- bronze, silver, and gold have no explicit responsibilities
- gold tables are fed directly from unstable raw landing logic
- merge semantics are unclear for CDC or late data
- maintenance tasks such as compaction are ignored
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 · 70 lines · 59 tokens per session scan A 853a8d782556
delta-lake-and-medallion-architecture is a skill published in the GitHub repository vaquarkhan/data-engineering-agent-skills (45 stars, last pushed 3mo ago), licensed MIT. It adds 59 tokens to every session and 568 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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