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 nextflowInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
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.
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
ReviewOur 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.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| nextflow (this skill)by K-Dense-AI | 100 | 46.4k | 48d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 110.3k | 1d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 79.1k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 99.8k | today | MCP Server |
| crawl4aiby unclecode | 100 | 87.1k | 4d ago | MCP 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.
Skill content
View source on GitHubname: 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
processtasks 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) +
-resumecaching + pinned pipeline revisions. - DSL2 is the modern, required syntax: modular
process/workflow/includedefinitions.
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
.nfscripts,nextflow.config, profiles, ornextflow_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.-resumereuses 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:, optionaldirectives(resources, container,publishDir,tag,errorStrategy), and ascript:/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 beincluded as subworkflows. The unnamedworkflow {}is the entry point. - Module: a
.nffile exposing processes/workflows viainclude { NAME } from './path'(supportsasaliasing). - Configuration:
nextflow.configsetsparams,processdirectives,executor, container engines, and namedprofiles. SelectorswithName:/withLabel:target specific processes. Seereferences/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. Seereferences/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
testfirst:-profile test,docker(orsingularity/conda) before real data — fast and catches environment problems. - Pin everything: pipeline revision (
-r),NXF_VER, and tool versions (containers). Don't runlatestfor science you'll publish. - Use
-resumeand understand caching: a task re-runs if its inputs, script, or container change. See cache-debugging inreferences/configuration.md. - Parameterize via config/params-file, not hardcoded paths. Keep
paramsand profiles innextflow.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 throughext.args(not hardcoded in the script); always include astub:block and nf-test tests; runnf-core pipelines lintandprettierbefore committing. - Right-size resources with
process_low/medium/highlabels anderrorStrategy 'retry'with dynamictask.attemptscaling 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 -> ... }),deffor all variables, andemit:-named outputs. Check withnextflow 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/withLabelselectors, executors (local/SLURM/cloud), caching/-resumeinternals, tracing/reports, thenextflowCLI.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— completenf-coreCLI reference (pipelines/modules/subworkflows), flags, and workflows.references/developing.md— authoring nf-core pipelines & modules: template layout, modulemain.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.
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
