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/nextflow

Build, run, and debug Nextflow data pipelines and nf-core workflows end to end. Use whenever the user mentions Nextflow, nf-core, .nf files, nextflow.config, DSL2, processes/channels/operators, samplesheets, or wants to run a community pipeline (e.g. nf-core/rnaseq,

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k-dense-ai-scientific-agent-skills
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Install
$ npx -y skills add k-dense-ai/claude-scientific-skills --skill nextflow --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/nextflow

Context preview

The summary Claude sees to decide when to auto-load this skill.

Build, run, and debug Nextflow data pipelines and nf-core workflows end to end. Use whenever the user mentions Nextflow, nf-core, .nf files, nextflow.config, DSL2, processes/channels/operators, samplesheets, or wants to run a community pipeline (e.g. nf-core/rnaseq,

SKILL.md

nextflow.SKILL.md
name: nextflow
description: Build, run, and debug Nextflow data pipelines and nf-core workflows end to end. Use whenever the user mentions Nextflow, nf-core, .nf files, nextflow.config, DSL2, processes/channels/operators, samplesheets, or wants to run a community pipeline (e.g. nf-core/rnaseq, nf-core/sarek), write or test a module/subworkflow with nf-test, configure executors/containers (Docker, Singularity/Apptainer, Conda, Wave), scale a workflow to HPC/SLURM or cloud (AWS Batch, Google Batch, Azure, Kubernetes), or debug a failed/-resume run. Make sure to use this skill for any reproducible scientific/bioinformatics workflow work even if the user does not say the word "Nextflow", and for authoring nf-core-compliant pipelines, modules, configs, and linting.
license: Apache-2.0
metadata:
  version: "1.2"
  skill-author: K-Dense Inc.

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**: per-task containers (Docker/Singularity/Apptainer/Conda/Wave) + `-resume` caching + pinned pipeline revisions.
  • **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.
  • Build a reproducible scientific/bioinformatics workflow (even if "Nextflow" is not named).
  • Understand processes, channels, operators, `take`/`emit`, `publishDir`, `ext.args`, meta maps.

Setup

Nextflow needs **Bash** and **Java 17 or newer** (17–25 supported). Verify with `java -version`.

# Install Nextflow (self-contained launcher)
curl -s https://get.nextflow.io | bash      # creates ./nextflow
sudo mv nextflow /usr/local/bin/             # put on PATH
nextflow info                                # verify

# Or via conda/bioconda (also gets a managed Java)
conda create -n nf -c bioconda -c conda-forge nextflow nf-core
# nf-core tools (Python) for creating/linting/running nf-core assets
uv pip install nf-core            # or: conda install -c bioconda nf-core
nf-core --version

Pin the engine for reproducibility: `export NXF_VER=24.10.0` (use an [edge] release only if needed). 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

Always smoke-test with the bundled `test` profile first; it uses tiny data and proves your environment works.

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

# 2. Real run: pin a revision (-r), pick a container engine, pass inputs
nextflow run nf-core/rnaseq -r 3.14.0 \
  -profile docker \
  --input samplesheet.csv \
  --genome GRCh38 \
  --outdir results \
  -resume
  • `-profile` (single dash) selects bundled config profiles; **combine** them comma-separated, e.g. `test,docker`. Container/infra profiles (`docker`, `singularity`, `conda`) are mutually exclusive — pick one.
  • `--input`, `--genome`, `--outdir` (double dash) are **pipeline** parameters. nf-core pipelines take a **samplesheet CSV**, not loose files.
  • `-resume` reuses cached results from the last run. `-r <version>` pins a release for reproducibility.

Use `nf-core pipelines launch <name>` for an interactive, schema-validated way to build the command and a `-params-file`. See `references/running-pipelines.md`.

Write a minimal pipeline

#!/usr/bin/env nextflow

process SAYHELLO {
    tag "$greeting"
    publishDir "results", mode: 'copy'

    input:
    val greeting

    output:
    path "${greeting}.txt"

    script:
    """
    echo '$greeting world' > ${greeting}.txt
    """
}

workflow {
    channel.of('hello', 'bonjour', 'hola') | SAYHELLO
}
nextflow run main.nf            # add -resume on reruns

The full language (processes, channels, operators, DSL2 workflows with `take`/`main`/`emit`, modules) is in `references/language.md`.

Core Concepts at a Glance

  • **Process**: a unit of work that runs a script (Bash by default). Declares `input:`, `output:`, optional `directives` (resources, container, `publishDir`, `tag`, `errorStrategy`), and a `script:`/`shell:`/`exec:` block. Each task runs in its own isolated work directory (`work/xx/yy…`).
  • **Channel*
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