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Skills IA DevOps

Découvrez les skills DevOps, comparez leurs dépôts et consultez leurs instructions.

Catégories: DevOps

5,089–5,112 sur 83,066

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GitHub

frontend-design

Swetrix

Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications. Generates creative, poli...

GitHub

flowmvi

respawn-app

FlowMVI usage guidance. Use when working with FlowMVI stores/containers, plugin pipelines, composing stores, decorators, or authoring plugins.

GitHub

bulk-rna-seq-deconvolution-with-bulk2single

Starlitnightly

Turn bulk RNA-seq cohorts into synthetic single-cell datasets using omicverse's Bulk2Single workflow for cell fraction estimation, beta-VAE generation, and quality control comparisons against reference scRNA-se...

GitHub

data-stats-analysis

Starlitnightly

Perform statistical tests, hypothesis testing, correlation analysis, and multiple testing corrections using scipy and statsmodels. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).

GitHub

single2spatial-spatial-mapping

Starlitnightly

Map scRNA-seq atlases onto spatial transcriptomics slides using omicverse's Single2Spatial workflow for deep-forest training, spot-level assessment, and marker visualisation.

GitHub

gsea-enrichment-analysis

Starlitnightly

Gene set enrichment analysis with correct geneset format handling. Critical guidance for loading pathway databases and running enrichment in OmicVerse.

GitHub

data-export-excel

Starlitnightly

Export analysis results, data tables, and formatted spreadsheets to Excel files using openpyxl. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).

GitHub

data-export-pdf

Starlitnightly

Create professional PDF reports with text, tables, and embedded images using reportlab. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).

GitHub

data-transform

Starlitnightly

Transform, clean, reshape, and preprocess data using pandas and numpy. Works with ANY LLM provider (GPT, Gemini, Claude, etc.).

Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.

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