nextflow-io
Official@nextflow-io
Portable, reproducible data-driven computational pipelines at scale
Agent Skills by nextflow-io
Showing 12 vetted skills indexed across 1 GitHub repositories.
nextflow-iostop-preview
Stop the training-mkdocs Docker container to terminate the MkDocs preview server.
nextflow-ioValidate Training Materials
Validate Nextflow training materials for structure, formatting, and content accuracy.
nextflow-ioTest Nextflow Example Script
Execute Nextflow scripts and verify outputs against documentation.
nextflow-ionew-lesson
Create numbered lesson pages with a templated Markdown structure.
nextflow-ioCheck Code Block Highlights
Validate hl_lines highlights in Markdown code blocks and report mismatches.
nextflow-ioadd-exercise
Insert formatted exercise and solution blocks into training lessons.
nextflow-ioDocker Environment Setup
Provision a reproducible Docker environment for Nextflow training examples.
nextflow-ioRun Tutorial Walkthrough
Execute tutorial commands and validate outputs against solutions.
nextflow-ioFind TODO and FIXME Comments
Detect and categorize TODO and FIXME comments in Markdown, Nextflow, and config files.
nextflow-ioCheck Inline Code Formatting
Validate inline code backticks and Groovy syntax highlighting in Markdown documents.
nextflow-ionew-module
Scaffold a complete training module structure with docs layout and navigation files.
nextflow-iopreview
Start a local MkDocs preview server via Docker or uv on port 8000.
Frequently Asked Questions About nextflow-io
FAQPage SchemaWhat specific tasks are enabled by these training resources?▼
These resources enable the creation of structured educational content, validation of Groovy-based computational logic, and verification of tutorial outputs. Users can scaffold new modules, insert formatted exercises, and ensure technical accuracy through automated checks of code blocks and inline syntax formatting.
Which personas benefit from these training capabilities?▼
Bioinformaticians, computational biologists, and technical instructors benefit from these capabilities. The resources are designed for engineers who need to maintain reproducible training environments and ensure that complex computational logic remains consistent across evolving documentation and instructional materials.
What are the prerequisites for running these training environments?▼
Execution requires a local environment capable of running Docker containers or the uv package manager. Users must have a system configured to handle MkDocs for documentation rendering and a runtime environment compatible with Nextflow and Groovy syntax for validating the provided computational examples.