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nextflow

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 pipelin…

Install / Use

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

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

100/100

Category

Automation

Supported Platforms

Universal

Our assessment of nextflow

nextflow scores 100/100 on our quality scale, 24th of 2,878 Automation skills we index (top 1%).

Its SKILL.md is 13 KB long, well organised into 19 sections with 5 code examples: a thorough specification that gives an agent plenty to work with.

With 46,441 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
30/30
Structure
20/20
Description
15/15
Adoption
20/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated about 2 months ago, so nextflow is actively maintained.
  • Our last check on 2026-10-22 found the source still online.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

Review

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands (1 minor note below). An AI review judged it risky: Line 40 instructs `curl -s https://get.nextflow.io | bash`, which is a skill/rules file telling the agent to pipe a remote script into a shell.

  • noteInstalls by piping a downloaded script into a shellline 40
    curl -s https://get.nextflow.io | bash # creates ./nextflow

AI review: risky

  • Line 40 instructs `curl -s https://get.nextflow.io | bash`, which is a skill/rules file telling the agent to pipe a remote script into a shell.
  • Other setup commands use package managers (`conda`, `uv pip`) and run standard Nextflow/nf-core tooling, which are normal for the domain.
  • No evidence of credential theft, destructive commands, permission bypasses, or proxy/API redirection.

AI review by kimi-k2.7-code on 2026-09-26. Automated pattern scan on 2026-09-26. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

nextflow compared with similar skills

nextflow has the highest quality score among these 4 similar skills, though 4 alternatives have been updated more recently.

SkillScoreStarsUpdatedFormat
nextflow (this skill)by K-Dense-AI10046.4k48d agoSKILL.md
Agent-Reachby Panniantong100110.3k1d agoCLAUDE.md
headroomby headroomlabs-ai10079.1ktodayCLAUDE.md
Scraplingby D4Vinci10099.8ktodayMCP Server
crawl4aiby unclecode10087.1k4d agoMCP Server

Frequently asked questions

How do I install nextflow?
Run npx skills add K-Dense-AI/scientific-agent-skills --skill nextflow. The install tabs above show the steps for each supported agent.
Which AI agents does nextflow work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is nextflow safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands (1 minor note below). An AI review judged it risky: Line 40 instructs curl -s https://get.nextflow.io | bash, which is a skill/rules file telling the agent to pipe a remote script into a shell. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is nextflow still maintained?
The repository was last updated about 2 months ago, so nextflow is actively maintained.

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: the async queues that connect processes. Queue channels are consumable streams; value channels hold a single reusable value. Created with factories like channel.of, channel.fromPath, channel.fromFilePairs, channel.value.
  • Operator: transforms/combines channels — map, filter, collect, groupTuple, join, combine, mix, flatten, branch, multiMap, splitCsv, view, set.
  • Workflow: composes processes. DSL2 workflows can declare take: (inputs), main: (logic), emit: (named outputs) and be included as subworkflows. The unnamed workflow {} is the entry point.
  • Module: a .nf file exposing processes/workflows via include { NAME } from './path' (supports as aliasing).
  • Configuration: nextflow.config sets params, process directives, executor, container engines, and named profiles. Selectors withName:/withLabel: target specific processes. See references/configuration.md.
  • meta map (nf-core): the convention of carrying a metadata map ([ id:'sample1', single_end:false ]) alongside files in input/output tuples so samples stay labeled through the pipeline. See references/developing.md.

nf-core tools CLI

nf-core tools (v3+) group subcommands under pipelines, modules, and subworkflows. (Bare forms like nf-core lint still work but warn — prefer the grouped form.)

| Command | Purpose | |---------|---------| | nf-core pipelines list | List/search nf-core pipelines (--json, keywords) | | nf-core pipelines create | Scaffold a new pipeline from the nf-core template | | nf-core pipelines launch <name> | Interactive, schema-driven run command + params file | | nf-core pipelines download <name> | Download pipeline + containers for offline/HPC use | | nf-core pipelines lint | Lint a pipeline against nf-core standards (run in repo root) | | nf-core pipelines schema build | Build/edit nextflow_schema.json via web GUI | | nf-core pipelines create-params-file <name> | Generate a documented YAML params file | | nf-core pipelines bump-version / sync | Bump version / sync with template updates | | nf-core modules list/info/install/update/remove | Manage modules from nf-core/modules | | nf-core modules create / lint / test | Author, lint, and nf-test a module | | nf-core modules patch / bump-versions | Patch an installed module / bump tool versions | | nf-core subworkflows install/create/lint/test | Same lifecycle for subworkflows |

Full command reference, flags, and examples: references/nf-core-tools.md.

Essential nextflow CLI

| Command | Purpose | |---------|---------| | nextflow run <pipeline> -profile <p> --outdir <dir> | Run a pipeline (path, .nf, or user/repo) | | -resume | Reuse cached results from prior run | | -r <rev> | Run a specific git revision/tag/branch | | -params-file params.yml | Supply parameters from YAML/JSON | | -c custom.config | Layer in an extra config file | | -with-report -with-trace -with-timeline -with-dag flow.html | Execution report, trace, timeline, DAG | | -stub-run | Run stub: blocks only (dry-run plumbing) | | nextflow log | Inspect past runs | | nextflow clean -f -before <run> | Delete old work/ data | | nextflow pull / drop / list / info <repo> | Manage cached remote pipelines |

Config, executors, caching internals, and tracing details: references/configuration.md.

Best Practices (high-value habits)

  • Always test first: -profile test,docker (or singularity/conda) before real data — fast and catches environment problems.
  • Pin everything: pipeline revision (-r), NXF_VER, and tool versions (containers). Don't run latest for science you'll publish.
  • Use -resume and understand caching: a task re-runs if its inputs, script, or container change. See cache-debugging in references/configuration.md.
  • Parameterize via config/params-file, not hardcoded paths. Keep params and profiles in nextflow.config.
  • One container/conda env per process; never rely on tools installed on the host.
  • For nf-core dev: reuse existing modules (nf-core modules install) before writing new ones; pass tool flags through ext.args (not hardcoded in the script); always include a stub: block and nf-test tests; run nf-core pipelines lint and prettier before committing.
  • Right-size resources with process_low/medium/high labels and errorStrategy 'retry' with dynamic task.attempt scaling instead of one giant request.
  • Write forward-compatible syntax: the strict-syntax parser becomes the default in Nextflow 26.04. Prefer lowercase channel.of(...), explicit closure params ({ v -> ... }), def for all variables, and emit:-named outputs. Check with nextflow lint.

Reference Files

Read the relevant file when you need depth — each is self-contained:

  • references/language.md — DSL2 language: processes, directives, channels, operators, workflows (take/emit), modules, dynamic resources, error handling.
  • references/configuration.md — nextflow.config, scopes, profiles, withName/withLabel selectors, executors (local/SLURM/cloud), caching/-resume internals, tracing/reports, the nextflow CLI.
  • references/containers.md — Docker, Singularity/Apptainer, Podman, Conda, Wave containers; choosing and enabling engines; common gotchas.
  • references/running-pipelines.md — finding/running nf-core pipelines, samplesheets, params files, reference genomes (iGenomes), offline runs, institutional configs, Seqera Platform.
  • references/nf-core-tools.md — complete nf-core CLI reference (pipelines/modules/subworkflows), flags, and workflows.
  • references/developing.md — authoring nf-core pipelines & modules: template layout, module main.nf/meta.yml, meta maps, ext.args/modules.config, subworkflows, resource labels, linting & Harshil alignment style.
  • references/testing.md — nf-test for modules/subworkflows/pipelines: test structure, asse

Truncated for display — read the full file on GitHub.

Related Skills

View on GitHub
GitHub Stars46.4k
CategoryAutomation
Updated1mo ago
Forks4.2k

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions