Agent skill · research science · k-dense-ai
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, 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.
Why this skill is useful
Adds executable scripts for running and debugging Nextflow pipelines, along with domain-specific knowledge for bioinformatics workflows.
What it needs
Requires conda, java, nextflow, nf-core installed locally. About 7k tokens when loaded. Last updated 2026-08-03. 32,849 stars on the source repository.
What this skill does
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 nextflowschema.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. Pin the engine for reproducibility: export NXFVER=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. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills k-dense-ai/nextflow