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data-engineering

Skill0 starsChanged 5 months agoNo licenceView on GitHub

Design, implement, test, debug, and review reliable batch data systems, including Python or SQL transformations, ETL/ELT pipelines, DuckDB workflows, incremental processing and watermarks, data models and warehouse schemas, file ingestion, data-quality checks, backfills, and reconciliation. Use when building or fixing a pipeline, model, or dataset that will run again — where the deliverable is the data system and its correctness guarantees, and where reruns, late data, and data loss are risks worth designing against. Not for one-off analysis of a single spreadsheet or CSV where the answer or a formatted file is the deliverable, not for application database schema migrations tied to app code (Rails, Django, Alembic), and not for streaming-engine or orchestrator internals such as Kafka topology, exactly-once sink configuration, schema-registry administration, or Airflow deployment.

21 other projects use a version of this.

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Projects with it also use qa-testing, api-documentation and 7 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • miketrombaSkill

    qa-testing

    Autonomously QA and verify the application using browser automation. Use when verifying code changes, testing features, validating bug fixes, or confirming any work done on the application. Triggers on requests to "test this", "verify this works", "QA this change", "make sure it works", or after implementing features that need validation.

    Also in 3 projects that use this

  • onejaejaeSkill

    api-documentation

    API 문서화 스킬. Notion과 Postman에 API 명세를 추가합니다. Use when documenting APIs, updating Notion database, or adding Postman requests.

    Also in 3 projects that use this

  • AnthropicSkill

    system-design

    Design systems, services, and architectures. Trigger with "design a system for", "how should we architect", "system design for", "what's the right architecture for", or when the user needs help with API design, data modeling, or service boundaries.

    Also in 4 projects that use this

  • OpenAISkill

    observability

    Vercel Observability expert guidance — Drains (logs, traces, speed insights, web analytics), Web Analytics, Speed Insights, runtime logs, custom events, OpenTelemetry integration, and monitoring dashboards. Use when instrumenting, debugging, or optimizing application performance and user experience on Vercel.

    Also in 4 projects that use this

  • AnthropicSkill

    documentation

    Write and maintain technical documentation. Trigger with "write docs for", "document this", "create a README", "write a runbook", "onboarding guide", or when the user needs help with any form of technical writing — API docs, architecture docs, or operational runbooks.

    Also in 3 projects that use this

  • Microsoft AzureSkill

    git-workflow

    Squad branching model: dev-first workflow with insiders preview channel

    Also in 3 projects that use this

The file

Show its rules and text

We split this skill into the rules it gives an agent

18 rules. 0 are common, 18 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 18 edited versions we read keep these.

  • 18

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 18 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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