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young-lillo
Perfil de criador do GitHub

young-lillo

Visão por repositório de 24 skills coletadas em 1 repositórios do GitHub.

skills coletadas
24
repositórios
1
atualizado
2026-06-13
explorador de repositórios

Repositórios e skills representativas

dv-cook
Desenvolvedores de software

End-to-end project execution wrapper for Data Visualization Kit. Use when the user types `$dv-cook` or wants to continue a project after `$dv-plan` with the context, dataset, and goals already locked.

2026-06-13
dv-data-visualize
Desenvolvedores de software

Build and refresh visualization layers for Data Visualization Kit projects. Use when the task is dashboard construction, chart refresh, visualization-path selection, dashboard QA, or project-scoped visualization delivery that must follow the kit visualization workflow and resolve to one selected tool path.

2026-06-13
dv-plan
Desenvolvedores de software

Start a new Data Visualization Kit project with structured intake and planning. Use when the user types `$dv-plan`, starts a new project, has a dataset but unclear scope, needs framework mapping, or needs one canonical project plan file before any downstream `$dv-*` workflow runs.

2026-06-13
dv-publish
Desenvolvedores de software

Publish wrapper for Data Visualization Kit. Use when the user types `$dv-publish` or needs to make a project git-ready, deployment-ready, and aligned with the kit's publish rules.

2026-05-26
pbip
Desenvolvedores de software

Use when working with Power BI Project files, PBIP structure, PBIR report JSON, TMDL semantic model files, definition.pbir bindings, report folders, model folders, or validation after Power BI file edits.

2026-05-26
power-bi
Desenvolvedores de software

Use when a Data Visualization Kit project chooses Power BI as the visualization path, or when the user asks to build, review, publish, or operate Power BI reports, dashboards, semantic models, PBIP/PBIR assets, DAX, Power BI Desktop, or Microsoft Fabric-backed report workflows.

2026-05-26
apache-superset
Desenvolvedores de software

Maintain and evolve existing Apache Superset analytics stacks (v6.x). Use for SQL Lab, datasets, charts, dashboards, RBAC, RLS, embedding via guest token API, REST API integration, Celery async, caching, Docker/Helm deployment, and migration planning toward Metabase or Grafana. Prefer only for legacy projects that already selected Superset. Requires 4GB+ RAM.

2026-04-21
metabase
Desenvolvedores de software

Build and operate Metabase for interactive BI dashboards, SQL exploration, models, metrics, questions, filters, permissions, embedding (static, guest, modular web components, React SDK), serialization/representation format, database metadata, and open-source self-hosted delivery. Use when the selected path is Metabase or when DV needs its default general BI stack.

2026-04-21
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