Nextflow
Automate repetitive workflows and reduce manual effort
Example: Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example: Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example: Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Time estimate: 15-45 minutes depending on use case complexity
Prerequisites
Submit your Claude Code skill and start earning
epx add K-Dense-AI/scientific-agent-skills --skill nextflowCompatible with
Supported agents
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, sample..."
| 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: "1.0" skill-author: K-Dense Inc. |
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:
process tasks connected by channels. Nextflow infers execution order and parallelism from data dependencies — there is no explicit scheduler to write.-resume caching + pinned pipeline revisions.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).
Use this skill when the user wants to:
.nf scripts, nextflow.config, profiles, or nextflow_schema.json.main.nf, meta.yml, tests/, nf-test).take/emit, publishDir, ext.args, meta maps.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
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.
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 |
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.
#!/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.
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.of, channel.fromPath, channel.fromFilePairs, channel.value.map, filter, collect, groupTuple, join, combine, mix, flatten, branch, multiMap, splitCsv, view, set.take: (inputs), main: (logic), emit: (named outputs) and be included as subworkflows. The unnamed workflow {} is the entry point..nf file exposing processes/workflows via include { NAME } from './path' (supports as aliasing).nextflow.config sets params, process directives, executor, container engines, and named profiles. Selectors withName:/withLabel: target specific processes. See references/configuration.md.[ 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 (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.
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.
test first: -profile test,docker (or singularity/conda) before real data — fast and catches environment problems.-r), NXF_VER, and tool versions (containers). Don't run latest for science you'll publish.-resume and understand caching: a task re-runs if its inputs, script, or container change. See cache-debugging in references/configuration.md.params and profiles in nextflow.config.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.process_low/medium/high labels and errorStrategy 'retry' with dynamic task.attempt scaling instead of one giant request.channel.of(...), explicit closure params ({ v -> ... }), def for all variables, and emit:-named outputs. Check with nextflow lint.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, assertions, snapshots, tags, running tests, CI.Official docs: Nextflow https://www.nextflow.io/docs/latest/ · nf-core https://nf-co.re/docs/ · Training https://training.nextflow.io/
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionnextflowExecute the skills CLI command in your project's root directory to begin installation:
epx add K-Dense-AI/scientific-agent-skills --skill nextflowFetches nextflow from K-Dense-AI/scientific-agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
.cursor/skills/nextflow
Restart Cursor to activate nextflow. Access via /nextflowin your agent's command palette.
Learn more:View source on GitHubSkills CLI docsAbout CursorWhat are agent skills?
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
statistical-analysis
K-Dense-AI/scientific-agent-skills · Science · same repo
hypothesis-generation
K-Dense-AI/scientific-agent-skills · Science · same repo
transformers
K-Dense-AI/scientific-agent-skills · Science · same repo
scientific-slides
K-Dense-AI/scientific-agent-skills · Science · same repo
scientific-visualization
K-Dense-AI/scientific-agent-skills · Science · same repo
pydeseq2
K-Dense-AI/scientific-agent-skills · Science · same repo
Useful defaults in nextflow — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: nextflow is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend nextflow for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
nextflow has been reliable in day-to-day use. Documentation quality is above average for community skills.
nextflow fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: nextflow is focused, and the summary matches what you get after install.
nextflow fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: nextflow is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend nextflow for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: nextflow is focused, and the summary matches what you get after install.
showing 1-10 of 38