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Deploy & cloud (DevOps)51k · #1914

nextflow

Lets your agent build and debug programming workflows called Nextflow. It's useful for managing and running complex data analysis pipelines.

What it does

Nextflow is a tool that helps build and run complex workflows for processing large amounts of data. It's widely used in fields like bioinformatics.

When to use it

  • ✓When you need to process a lot of data in an organized and repeatable way.
  • ✓If you work in bioinformatics and need to analyze genetic data.
  • ✓To automate data analysis tasks that need to be done many times.

Example of what to ask your AI

“How do I run an RNA-seq analysis pipeline using nf-core?”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/K-Dense-AI/scientific-agent-skills/blob/main/skills/nextflow/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/K-Dense-AI/scientific-agent-skills/blob/main/skills/nextflow/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

Nextflow organizes your tasks into 'processes' that communicate via 'channels'. It automatically decides the order of execution and how many tasks to run concurrently, based on data dependencies.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add K-Dense-AI/scientific-agent-skills --skill nextflow

Or download just the file:

curl -L https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/main/skills/nextflow/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Nextflow

Overview

Nextflow is a workflow language and runtime for building reproducible, portable, scalable data pipelines. It is dominant in bioinformatics but works for any data-heavy computation. nf-core is a community curating production-grade Nextflow pipelines, reusable modules, and the nf-core tooling on top of Nextflow.

Key ideas:

  • Dataflow programming: pipelines are process tasks connected by channels. Nextflow infers execution order and parallelism from data dependencies — there is no explicit scheduler to write.
  • Write once, run anywhere: the same pipeline runs locally, on HPC (SLURM, SGE, LSF, PBS), and on cloud (AWS Batch, Google Batch, Azure Batch, Kubernetes) by changing config/profiles, not code.
  • Reproducibility: pinned software environments and pipeline revisions, immutable inputs/references, recorded parameters and seeds. -resume is a computational cache, not scientific validation. Conda is an environment manager; Wave resolves/builds images rather than executing them.
  • DSL2 is the modern, required syntax: modular process/workflow/include definitions.

This skill covers both running existing pipelines and developing your own (Nextflow language + nf-core conventions, testing with nf-test, configuration, and deployment).

When to Use This Skill

Use this skill when the user wants to:

  • Run an nf-core or custom Nextflow pipeline, or debug a failing/resuming run.
  • Write or modify .nf scripts, nextflow.config, profiles, or nextflow_schema.json.
  • Author or test nf-core-style modules/subworkflows (main.nf, meta.yml, tests/, nf-test).
  • Configure executors, containers, or resources; scale to HPC or cloud.
  • Implement a scientific workflow in Nextflow or adapt an existing nf-core pipeline.
  • Understand processes, channels, operators, take/emit, publishDir, ext.args, meta maps.

Setup

This review targets stable Nextflow 26.04.6, nf-core tools 4.1.0, and nf-test 0.9.5. Nextflow needs Bash 3.2+ and Java 17–26; verify java -version (a launcher on PATH does not prove a runtime is installed). The strict parser is the default in 26.04. See release notes and the 26.04 migration guide. Stable and edge documentation can differ; do not use a preview feature without its version/flag.

# Install Nextflow (self-installing launcher)
export NXF_VER=26.04.6
curl -fsSL https://get.nextflow.io -o install-nextflow.sh
# Review the installer before executing it.
bash < install-nextflow.sh
mkdir -p "$HOME/.local/bin"
mv nextflow "$HOME/.local/bin/"
export PATH="$HOME/.local/bin:$PATH"
nextflow info                                # verify

# Alternative (illustrative; confirm package availability and Java compatibility)
conda create -n nf -c conda-forge -c bioconda nextflow=26.04.6 nf-core=4.1.0
# nf-core tools (Python) for creating/linting/running nf-core assets
uv tool install "nf-core==4.1.0"
nf-core --version

Pin the engine for reproducibility: export NXF_VER=26.04.6; check the selected pipeline release’s engine constraint before upgrading. Use edge only for a required, explicitly tested feature. For air-gapped/HPC, see references/running-pipelines.md (offline mode) and references/configuration.md.

Two Modes of Work

Decide which path the user is on — it changes everything:

Goal Start here
Run an existing pipeline (nf-core or a .nf you were given) references/running-pipelines.md
Develop a new pipeline / module / subworkflow references/language.md + references/developing.md
Configure / scale (HPC, cloud, containers, resources) references/configuration.md + references/containers.md
Test modules/pipelines references/testing.md

Quick Start

Run an nf-core pipeline

Use the selected release’s small test profile first after checking its resource/download requirements. A passing smoke test verifies that configuration and fixture, not scientific accuracy or full-scale capacity. The following RNA-seq examples are illustrative; no biological pipeline or containers were run in this review.

# 1. Confirm setup works (downloads pipeline + tiny test data)
nextflow run nf-core/rnaseq -r 3.27.0 -profile test,docker --outdir test_results


…
FAQ

What is nf-core?

nf-core is a community that builds and shares ready-to-use workflows made with Nextflow, simplifying common data analysis tasks.

How does Nextflow ensure results are reliable?

It can pin exact versions of software and data used, and record all parameters, ensuring the analysis can be repeated exactly the same way in the future.

Can I use Nextflow on my computer and also on supercomputers?

Yes, Nextflow is designed to run in different environments, from your personal computer to large computer clusters (HPC) or the cloud, just by changing the configuration, not the code.

Details

Original description by the author

Builds, runs, and debugs Nextflow DSL2 pipelines and nf-core workflows. Use for Nextflow, nf-core, .nf files, nextflow.config, processes/channels/operators, samplesheets, nf-test, modules/subworkflows, container and executor configuration, HPC/SLURM or cloud deployment, and failed or resumed pipeline runs.

repo: K-Dense-AI/scientific-agent-skills

Popularity

GitHub stars
51k
Ranking position
#1914
License
MIT
Updated
10/15/2026

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