dataops

dataops

Field	Value
Kind	skill
Source	.github/skills/data-science-engineering/dataops
Invocation	Loaded on demand by referencing agents
Interactive	No

What it does

DataOps and DS/MLOps testing reference for data tiering, Bronze-to-Silver validation placement, pipeline invariants, pytest categories, and validation-versus-drift. Use when designing, reviewing, or generating data pipelines, transformation code, data validation, or data-science test suites.

When to use it

Reach for this skill when the work touches data movement, transformation, or the tests that guard it:

• Designing or reviewing a tiered data layout and deciding which storage areas are pipeline tiers versus operational areas.
• Deciding where schema and quality validation belongs relative to a Bronze-to-Silver boundary, and why replayability constrains that placement.
• Writing or reviewing pytest suites for data-science and MLOps code, including which outside calls to mock and which to leave real.
• Distinguishing a data-validation failure from model or data drift, and routing each to its own remediation path.

Choose a different asset when:

• The question is about telemetry naming, span attributes, or metric conventions. Use the telemetry-foundations skill.
• The question is about data classification, personal-data handling, or DPIA thresholds. Use the privacy-standards skill.
• The question is about designing an experiment or forming a hypothesis. Use the experiment-design skill.

Example usage

Ask an agent that loads this skill to review a pipeline change:

Review this Bronze-to-Silver notebook. Where should schema validation live,
and what does that imply for replay?

The skill grounds the answer in its reference pack: validation runs at the Bronze-to-Silver boundary so Bronze retains the raw landed record, which preserves two distinct replay paths (replaying to exercise changed validation logic, and replaying to recover from a transformation defect).

It also flags the notebook-extraction trigger when transformation logic outgrows an interactive cell, and separates transformation code from data-access code so the transformation is unit-testable without mocking storage.