[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6QFAQE7SVT7FYB63SW2D20Q":3,"skill-same:01M6QFAQE7SVT7FYB63SW2D20Q":109},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":26,"publishedAt":46,"linkOnly":47,"markdownContent":48,"markdownBody":49,"frontMatter":50,"refName":56,"commitSha":57,"skillDirectory":58,"forksCount":14,"repositoryHtmlUrl":59,"repositoryHomepageUrl":60,"ownerHtmlUrl":61,"ownerBlogUrl":62,"ownerDescription":63,"updatedAt":64,"install":65,"resources":78},"01M6QFAQE7SVT7FYB63SW2D20Q","nextflow",null,"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\u002Fchannels\u002Foperators, samplesheets, or wants to run a community pipeline (e.g. nf-core\u002Frnaseq, nf-core\u002Fsarek), write or test a module\u002Fsubworkflow with nf-test, configure executors\u002Fcontainers (Docker, Singularity\u002FApptainer, Conda, Wave), scale a workflow to HPC\u002FSLURM or cloud (AWS Batch, Google Batch, Azure, Kubernetes), or debug a failed\u002F-resume run. Make sure to use this skill for any reproducible scientific\u002Fbioinformatics workflow work even if the user does not say the word \"Nextflow\", and for authoring nf-core-compliant pipelines, modules, configs, and linting.","Tashima-Tarsh\u002FDisha6.6","Tashima-Tarsh","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F269906498?v=4","01M6PBH98X03XERH0HFT4PFB1P","NITISH KUMAR","01M6PBH9DA0M6KM3Z12P848F0K",0,"Apache-2.0","https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fkal-nextflow\u002FSKILL.md",[18,23],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000011","运维与部署","SCENARIO","使用场景",{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000023","Skill与智能体开发",[5,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45],"modules","for","rnaseq","scientific","conda","module","authoring","operators","files","google","use","write","Reproducible","Slurm","batch","run","debug","config","workflows","2026-11-10 10:12:30",false,"---\nname: nextflow\ndescription: 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\u002Fchannels\u002Foperators, samplesheets, or wants to run a community pipeline (e.g. nf-core\u002Frnaseq, nf-core\u002Fsarek), write or test a module\u002Fsubworkflow with nf-test, configure executors\u002Fcontainers (Docker, Singularity\u002FApptainer, Conda, Wave), scale a workflow to HPC\u002FSLURM or cloud (AWS Batch, Google Batch, Azure, Kubernetes), or debug a failed\u002F-resume run. Make sure to use this skill for any reproducible scientific\u002Fbioinformatics workflow work even if the user does not say the word \"Nextflow\", and for authoring nf-core-compliant pipelines, modules, configs, and linting.\nlicense: Apache-2.0\nmetadata:\n  version: '1.2'\n  category: life-sciences\n  maintainer: Kalaris Labs\n  tags: Nextflow, nf-core, bioinformatics pipelines, workflow management, genomics\n---\n\n# Nextflow\n\n## Overview\n\nNextflow 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.\n\nKey ideas:\n- **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.\n- **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\u002Fprofiles, not code.\n- **Reproducibility**: per-task containers (Docker\u002FSingularity\u002FApptainer\u002FConda\u002FWave) + `-resume` caching + pinned pipeline revisions.\n- **DSL2** is the modern, required syntax: modular `process`\u002F`workflow`\u002F`include` definitions.\n\nThis skill covers both **running** existing pipelines and **developing** your own (Nextflow language + nf-core conventions, testing with nf-test, configuration, and deployment).\n\n## When to Use This Skill\n\nUse this skill when the user wants to:\n- Run an nf-core or custom Nextflow pipeline, or debug a failing\u002Fresuming run.\n- Write or modify `.nf` scripts, `nextflow.config`, profiles, or `nextflow_schema.json`.\n- Author or test nf-core-style modules\u002Fsubworkflows (`main.nf`, `meta.yml`, `tests\u002F`, nf-test).\n- Configure executors, containers, or resources; scale to HPC or cloud.\n- Build a reproducible scientific\u002Fbioinformatics workflow (even if \"Nextflow\" is not named).\n- Understand processes, channels, operators, `take`\u002F`emit`, `publishDir`, `ext.args`, meta maps.\n\n## Setup\n\nNextflow needs **Bash** and **Java 17 or newer** (17–25 supported). Verify with `java -version`.\n\n```bash\n# Install Nextflow (self-contained launcher)\ncurl -s https:\u002F\u002Fget.nextflow.io | bash      # creates .\u002Fnextflow\nsudo mv nextflow \u002Fusr\u002Flocal\u002Fbin\u002F             # put on PATH\nnextflow info                                # verify\n\n# Or via conda\u002Fbioconda (also gets a managed Java)\nconda create -n nf -c bioconda -c conda-forge nextflow nf-core\n```\n\n```bash\n# nf-core tools (Python) for creating\u002Flinting\u002Frunning nf-core assets\nuv pip install nf-core            # or: conda install -c bioconda nf-core\nnf-core --version\n```\n\nPin the engine for reproducibility: `export NXF_VER=24.10.0` (use an [edge] release only if needed). For air-gapped\u002FHPC, see `references\u002Frunning-pipelines.md` (offline mode) and `references\u002Fconfiguration.md`.\n\n## Two Modes of Work\n\nDecide which path the user is on — it changes everything:\n\n| Goal | Start here |\n|------|-----------|\n| **Run** an existing pipeline (nf-core or a `.nf` you were given) | `references\u002Frunning-pipelines.md` |\n| **Develop** a new pipeline \u002F module \u002F subworkflow | `references\u002Flanguage.md` + `references\u002Fdeveloping.md` |\n| **Configure \u002F scale** (HPC, cloud, containers, resources) | `references\u002Fconfiguration.md` + `references\u002Fcontainers.md` |\n| **Test** modules\u002Fpipelines | `references\u002Ftesting.md` |\n\n## Quick Start\n\n### Run an nf-core pipeline\n\nAlways smoke-test with the bundled `test` profile first; it uses tiny data and proves your environment works.\n\n```bash\n# 1. Confirm setup works (downloads pipeline + tiny test data)\nnextflow run nf-core\u002Frnaseq -profile test,docker --outdir results\n\n# 2. Real run: pin a revision (-r), pick a container engine, pass inputs\nnextflow run nf-core\u002Frnaseq -r 3.14.0 \\\n  -profile docker \\\n  --input samplesheet.csv \\\n  --genome GRCh38 \\\n  --outdir results \\\n  -resume\n```\n\n- `-profile` (single dash) selects bundled config profiles; **combine** them comma-separated, e.g. `test,docker`. Container\u002Finfra profiles (`docker`, `singularity`, `conda`) are mutually exclusive — pick one.\n- `--input`, `--genome`, `--outdir` (double dash) are **pipeline** parameters. nf-core pipelines take a **samplesheet CSV**, not loose files.\n- `-resume` reuses cached results from the last run. `-r \u003Cversion>` pins a release for reproducibility.\n\nUse `nf-core pipelines launch \u003Cname>` for an interactive, schema-validated way to build the command and a `-params-file`. See `references\u002Frunning-pipelines.md`.\n\n### Write a minimal pipeline\n\n```nextflow\n#!\u002Fusr\u002Fbin\u002Fenv nextflow\n\nprocess SAYHELLO {\n    tag \"$greeting\"\n    publishDir \"results\", mode: 'copy'\n\n    input:\n    val greeting\n\n    output:\n    path \"${greeting}.txt\"\n\n    script:\n    \"\"\"\n    echo '$greeting world' > ${greeting}.txt\n    \"\"\"\n}\n\nworkflow {\n    channel.of('hello', 'bonjour', 'hola') | SAYHELLO\n}\n```\n\n```bash\nnextflow run main.nf            # add -resume on reruns\n```\n\nThe full language (processes, channels, operators, DSL2 workflows with `take`\u002F`main`\u002F`emit`, modules) is in `references\u002Flanguage.md`.\n\n## Core Concepts at a Glance\n\n- **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:`\u002F`shell:`\u002F`exec:` block. Each task runs in its own isolated work directory (`work\u002Fxx\u002Fyy…`).\n- **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`.\n- **Operator**: transforms\u002Fcombines channels — `map`, `filter`, `collect`, `groupTuple`, `join`, `combine`, `mix`, `flatten`, `branch`, `multiMap`, `splitCsv`, `view`, `set`.\n- **Workflow**: composes processes. DSL2 workflows can declare `take:` (inputs), `main:` (logic), `emit:` (named outputs) and be `include`d as subworkflows. The unnamed `workflow {}` is the entry point.\n- **Module**: a `.nf` file exposing processes\u002Fworkflows via `include { NAME } from '.\u002Fpath'` (supports `as` aliasing).\n- **Configuration**: `nextflow.config` sets `params`, `process` directives, `executor`, container engines, and named `profiles`. Selectors `withName:`\u002F`withLabel:` target specific processes. See `references\u002Fconfiguration.md`.\n- **meta map** (nf-core): the convention of carrying a metadata map (`[ id:'sample1', single_end:false ]`) alongside files in input\u002Foutput tuples so samples stay labeled through the pipeline. See `references\u002Fdeveloping.md`.\n\n## nf-core tools CLI\n\nnf-core tools (v3+) group subcommands under `pipelines`, `modules`, and `subworkflows`. (Bare forms like `nf-core lint` still work but warn — prefer the grouped form.)\n\n| Command | Purpose |\n|---------|---------|\n| `nf-core pipelines list` | List\u002Fsearch nf-core pipelines (`--json`, keywords) |\n| `nf-core pipelines create` | Scaffold a new pipeline from the nf-core template |\n| `nf-core pipelines launch \u003Cname>` | Interactive, schema-driven run command + params file |\n| `nf-core pipelines download \u003Cname>` | Download pipeline + containers for offline\u002FHPC use |\n| `nf-core pipelines lint` | Lint a pipeline against nf-core standards (run in repo root) |\n| `nf-core pipelines schema build` | Build\u002Fedit `nextflow_schema.json` via web GUI |\n| `nf-core pipelines create-params-file \u003Cname>` | Generate a documented YAML params file |\n| `nf-core pipelines bump-version` \u002F `sync` | Bump version \u002F sync with template updates |\n| `nf-core modules list\u002Finfo\u002Finstall\u002Fupdate\u002Fremove` | Manage modules from nf-core\u002Fmodules |\n| `nf-core modules create` \u002F `lint` \u002F `test` | Author, lint, and nf-test a module |\n| `nf-core modules patch` \u002F `bump-versions` | Patch an installed module \u002F bump tool versions |\n| `nf-core subworkflows install\u002Fcreate\u002Flint\u002Ftest` | Same lifecycle for subworkflows |\n\nFull command reference, flags, and examples: `references\u002Fnf-core-tools.md`.\n\n## Essential `nextflow` CLI\n\n| Command | Purpose |\n|---------|---------|\n| `nextflow run \u003Cpipeline> -profile \u003Cp> --outdir \u003Cdir>` | Run a pipeline (path, `.nf`, or `user\u002Frepo`) |\n| `-resume` | Reuse cached results from prior run |\n| `-r \u003Crev>` | Run a specific git revision\u002Ftag\u002Fbranch |\n| `-params-file params.yml` | Supply parameters from YAML\u002FJSON |\n| `-c custom.config` | Layer in an extra config file |\n| `-with-report -with-trace -with-timeline -with-dag flow.html` | Execution report, trace, timeline, DAG |\n| `-stub-run` | Run `stub:` blocks only (dry-run plumbing) |\n| `nextflow log` | Inspect past runs |\n| `nextflow clean -f -before \u003Crun>` | Delete old `work\u002F` data |\n| `nextflow pull \u002F drop \u002F list \u002F info \u003Crepo>` | Manage cached remote pipelines |\n\nConfig, executors, caching internals, and tracing details: `references\u002Fconfiguration.md`.\n\n## Best Practices (high-value habits)\n\n- **Always `test` first**: `-profile test,docker` (or `singularity`\u002F`conda`) before real data — fast and catches environment problems.\n- **Pin everything**: pipeline revision (`-r`), `NXF_VER`, and tool versions (containers). Don't run `latest` for science you'll publish.\n- **Use `-resume`** and understand caching: a task re-runs if its inputs, script, or container change. See cache-debugging in `references\u002Fconfiguration.md`.\n- **Parameterize via config\u002Fparams-file**, not hardcoded paths. Keep `params` and profiles in `nextflow.config`.\n- **One container\u002Fconda env per process**; never rely on tools installed on the host.\n- **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.\n- **Right-size resources** with `process_low\u002Fmedium\u002Fhigh` labels and `errorStrategy 'retry'` with dynamic `task.attempt` scaling instead of one giant request.\n- **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`.\n\n## Reference Files\n\nRead the relevant file when you need depth — each is self-contained:\n\n- `references\u002Flanguage.md` — DSL2 language: processes, directives, channels, operators, workflows (`take`\u002F`emit`), modules, dynamic resources, error handling.\n- `references\u002Fconfiguration.md` — `nextflow.config`, scopes, `profiles`, `withName`\u002F`withLabel` selectors, executors (local\u002FSLURM\u002Fcloud), caching\u002F`-resume` internals, tracing\u002Freports, the `nextflow` CLI.\n- `references\u002Fcontainers.md` — Docker, Singularity\u002FApptainer, Podman, Conda, Wave containers; choosing and enabling engines; common gotchas.\n- `references\u002Frunning-pipelines.md` — finding\u002Frunning nf-core pipelines, samplesheets, params files, reference genomes (iGenomes), offline runs, institutional configs, Seqera Platform.\n- `references\u002Fnf-core-tools.md` — complete `nf-core` CLI reference (pipelines\u002Fmodules\u002Fsubworkflows), flags, and workflows.\n- `references\u002Fdeveloping.md` — authoring nf-core pipelines & modules: template layout, module `main.nf`\u002F`meta.yml`, meta maps, `ext.args`\u002F`modules.config`, subworkflows, resource labels, linting & Harshil alignment style.\n- `references\u002Ftesting.md` — nf-test for modules\u002Fsubworkflows\u002Fpipelines: test structure, assertions, snapshots, tags, running tests, CI.\n\nOfficial docs: Nextflow https:\u002F\u002Fwww.nextflow.io\u002Fdocs\u002Flatest\u002F · nf-core https:\u002F\u002Fnf-co.re\u002Fdocs\u002F · Training https:\u002F\u002Ftraining.nextflow.io\u002F\n\n## Agent operating procedure\n\n1. **Check the environment.** Confirm tool versions, the reference genome\u002Fannotation build and the input formats (FASTQ, BAM, VCF, h5ad).\n2. **Pin down the inputs.** Confirm formats, identifiers and parameters from the data or the user. Ask rather than guess any value that changes the result.\n3. **Run a small version first.** Run the pipeline on a small subset (one sample, one chromosome, a few thousand cells) first.\n4. **Execute the full task** using the instructions and references above.\n5. **Validate the result.** Check QC metrics, sample identities, genome build consistency and batch effects before interpreting results.\n6. **Report.** State what was run (versions, commands, parameters), what was checked, and what is still uncertain.\n\n| If this happens | Do this |\n|---|---|\n| Genome builds or identifiers do not match between inputs | Stop and harmonize (liftover, ID mapping) before continuing. |\n| A function, flag or endpoint in these instructions is missing in the installed version | Check the installed version's own documentation (`help()`, `--help`, official docs), adapt, and tell the user. Never invent an API. |\n| A required input, identifier or parameter is ambiguous | Ask the user, or state the assumption explicitly before running. |\n\n**Integrity rules**\n\n- Never fabricate results, parameters, identifiers, citations or statistics. If something cannot be run or verified, say so plainly.\n- Do not interpret biological significance beyond what the statistics support; report multiple-testing correction.\n- Treat version-specific details here as possibly outdated: confirm them against the official documentation for the installed version.\n- Ask before actions that cost money, consume shared GPUs or cloud quota, touch personal or patient data, or cannot be undone.\n\n## Related skills\n\n- `pacsomatic`: Operator toolkit for nf-core\u002Fpacsomatic matched tumor-normal workflows from BAM inputs.\n- `bulk-rnaseq`: End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp\u002FTrim Galore), alignment and quantificat…\n- `latchbio-integration`: Build, register, debug, and operate bioinformatics workflows on Latch using the Python SDK, CLI, Latch Data and Registry, Nextflow, Snakema…\n","# Nextflow\n\n## Overview\n\nNextflow 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.\n\nKey ideas:\n- **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.\n- **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\u002Fprofiles, not code.\n- **Reproducibility**: per-task containers (Docker\u002FSingularity\u002FApptainer\u002FConda\u002FWave) + `-resume` caching + pinned pipeline revisions.\n- **DSL2** is the modern, required syntax: modular `process`\u002F`workflow`\u002F`include` definitions.\n\nThis skill covers both **running** existing pipelines and **developing** your own (Nextflow language + nf-core conventions, testing with nf-test, configuration, and deployment).\n\n## When to Use This Skill\n\nUse this skill when the user wants to:\n- Run an nf-core or custom Nextflow pipeline, or debug a failing\u002Fresuming run.\n- Write or modify `.nf` scripts, `nextflow.config`, profiles, or `nextflow_schema.json`.\n- Author or test nf-core-style modules\u002Fsubworkflows (`main.nf`, `meta.yml`, `tests\u002F`, nf-test).\n- Configure executors, containers, or resources; scale to HPC or cloud.\n- Build a reproducible scientific\u002Fbioinformatics workflow (even if \"Nextflow\" is not named).\n- Understand processes, channels, operators, `take`\u002F`emit`, `publishDir`, `ext.args`, meta maps.\n\n## Setup\n\nNextflow needs **Bash** and **Java 17 or newer** (17–25 supported). Verify with `java -version`.\n\n```bash\n# Install Nextflow (self-contained launcher)\ncurl -s https:\u002F\u002Fget.nextflow.io | bash      # creates .\u002Fnextflow\nsudo mv nextflow \u002Fusr\u002Flocal\u002Fbin\u002F             # put on PATH\nnextflow info                                # verify\n\n# Or via conda\u002Fbioconda (also gets a managed Java)\nconda create -n nf -c bioconda -c conda-forge nextflow nf-core\n```\n\n```bash\n# nf-core tools (Python) for creating\u002Flinting\u002Frunning nf-core assets\nuv pip install nf-core            # or: conda install -c bioconda nf-core\nnf-core --version\n```\n\nPin the engine for reproducibility: `export NXF_VER=24.10.0` (use an [edge] release only if needed). For air-gapped\u002FHPC, see `references\u002Frunning-pipelines.md` (offline mode) and `references\u002Fconfiguration.md`.\n\n## Two Modes of Work\n\nDecide which path the user is on — it changes everything:\n\n| Goal | Start here |\n|------|-----------|\n| **Run** an existing pipeline (nf-core or a `.nf` you were given) | `references\u002Frunning-pipelines.md` |\n| **Develop** a new pipeline \u002F module \u002F subworkflow | `references\u002Flanguage.md` + `references\u002Fdeveloping.md` |\n| **Configure \u002F scale** (HPC, cloud, containers, resources) | `references\u002Fconfiguration.md` + `references\u002Fcontainers.md` |\n| **Test** modules\u002Fpipelines | `references\u002Ftesting.md` |\n\n## Quick Start\n\n### Run an nf-core pipeline\n\nAlways smoke-test with the bundled `test` profile first; it uses tiny data and proves your environment works.\n\n```bash\n# 1. Confirm setup works (downloads pipeline + tiny test data)\nnextflow run nf-core\u002Frnaseq -profile test,docker --outdir results\n\n# 2. Real run: pin a revision (-r), pick a container engine, pass inputs\nnextflow run nf-core\u002Frnaseq -r 3.14.0 \\\n  -profile docker \\\n  --input samplesheet.csv \\\n  --genome GRCh38 \\\n  --outdir results \\\n  -resume\n```\n\n- `-profile` (single dash) selects bundled config profiles; **combine** them comma-separated, e.g. `test,docker`. Container\u002Finfra profiles (`docker`, `singularity`, `conda`) are mutually exclusive — pick one.\n- `--input`, `--genome`, `--outdir` (double dash) are **pipeline** parameters. nf-core pipelines take a **samplesheet CSV**, not loose files.\n- `-resume` reuses cached results from the last run. `-r \u003Cversion>` pins a release for reproducibility.\n\nUse `nf-core pipelines launch \u003Cname>` for an interactive, schema-validated way to build the command and a `-params-file`. See `references\u002Frunning-pipelines.md`.\n\n### Write a minimal pipeline\n\n```nextflow\n#!\u002Fusr\u002Fbin\u002Fenv nextflow\n\nprocess SAYHELLO {\n    tag \"$greeting\"\n    publishDir \"results\", mode: 'copy'\n\n    input:\n    val greeting\n\n    output:\n    path \"${greeting}.txt\"\n\n    script:\n    \"\"\"\n    echo '$greeting world' > ${greeting}.txt\n    \"\"\"\n}\n\nworkflow {\n    channel.of('hello', 'bonjour', 'hola') | SAYHELLO\n}\n```\n\n```bash\nnextflow run main.nf            # add -resume on reruns\n```\n\nThe full language (processes, channels, operators, DSL2 workflows with `take`\u002F`main`\u002F`emit`, modules) is in `references\u002Flanguage.md`.\n\n## Core Concepts at a Glance\n\n- **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:`\u002F`shell:`\u002F`exec:` block. Each task runs in its own isolated work directory (`work\u002Fxx\u002Fyy…`).\n- **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`.\n- **Operator**: transforms\u002Fcombines channels — `map`, `filter`, `collect`, `groupTuple`, `join`, `combine`, `mix`, `flatten`, `branch`, `multiMap`, `splitCsv`, `view`, `set`.\n- **Workflow**: composes processes. DSL2 workflows can declare `take:` (inputs), `main:` (logic), `emit:` (named outputs) and be `include`d as subworkflows. The unnamed `workflow {}` is the entry point.\n- **Module**: a `.nf` file exposing processes\u002Fworkflows via `include { NAME } from '.\u002Fpath'` (supports `as` aliasing).\n- **Configuration**: `nextflow.config` sets `params`, `process` directives, `executor`, container engines, and named `profiles`. Selectors `withName:`\u002F`withLabel:` target specific processes. See `references\u002Fconfiguration.md`.\n- **meta map** (nf-core): the convention of carrying a metadata map (`[ id:'sample1', single_end:false ]`) alongside files in input\u002Foutput tuples so samples stay labeled through the pipeline. See `references\u002Fdeveloping.md`.\n\n## nf-core tools CLI\n\nnf-core tools (v3+) group subcommands under `pipelines`, `modules`, and `subworkflows`. (Bare forms like `nf-core lint` still work but warn — prefer the grouped form.)\n\n| Command | Purpose |\n|---------|---------|\n| `nf-core pipelines list` | List\u002Fsearch nf-core pipelines (`--json`, keywords) |\n| `nf-core pipelines create` | Scaffold a new pipeline from the nf-core template |\n| `nf-core pipelines launch \u003Cname>` | Interactive, schema-driven run command + params file |\n| `nf-core pipelines download \u003Cname>` | Download pipeline + containers for offline\u002FHPC use |\n| `nf-core pipelines lint` | Lint a pipeline against nf-core standards (run in repo root) |\n| `nf-core pipelines schema build` | Build\u002Fedit `nextflow_schema.json` via web GUI |\n| `nf-core pipelines create-params-file \u003Cname>` | Generate a documented YAML params file |\n| `nf-core pipelines bump-version` \u002F `sync` | Bump version \u002F sync with template updates |\n| `nf-core modules list\u002Finfo\u002Finstall\u002Fupdate\u002Fremove` | Manage modules from nf-core\u002Fmodules |\n| `nf-core modules create` \u002F `lint` \u002F `test` | Author, lint, and nf-test a module |\n| `nf-core modules patch` \u002F `bump-versions` | Patch an installed module \u002F bump tool versions |\n| `nf-core subworkflows install\u002Fcreate\u002Flint\u002Ftest` | Same lifecycle for subworkflows |\n\nFull command reference, flags, and examples: `references\u002Fnf-core-tools.md`.\n\n## Essential `nextflow` CLI\n\n| Command | Purpose |\n|---------|---------|\n| `nextflow run \u003Cpipeline> -profile \u003Cp> --outdir \u003Cdir>` | Run a pipeline (path, `.nf`, or `user\u002Frepo`) |\n| `-resume` | Reuse cached results from prior run |\n| `-r \u003Crev>` | Run a specific git revision\u002Ftag\u002Fbranch |\n| `-params-file params.yml` | Supply parameters from YAML\u002FJSON |\n| `-c custom.config` | Layer in an extra config file |\n| `-with-report -with-trace -with-timeline -with-dag flow.html` | Execution report, trace, timeline, DAG |\n| `-stub-run` | Run `stub:` blocks only (dry-run plumbing) |\n| `nextflow log` | Inspect past runs |\n| `nextflow clean -f -before \u003Crun>` | Delete old `work\u002F` data |\n| `nextflow pull \u002F drop \u002F list \u002F info \u003Crepo>` | Manage cached remote pipelines |\n\nConfig, executors, caching internals, and tracing details: `references\u002Fconfiguration.md`.\n\n## Best Practices (high-value habits)\n\n- **Always `test` first**: `-profile test,docker` (or `singularity`\u002F`conda`) before real data — fast and catches environment problems.\n- **Pin everything**: pipeline revision (`-r`), `NXF_VER`, and tool versions (containers). Don't run `latest` for science you'll publish.\n- **Use `-resume`** and understand caching: a task re-runs if its inputs, script, or container change. See cache-debugging in `references\u002Fconfiguration.md`.\n- **Parameterize via config\u002Fparams-file**, not hardcoded paths. Keep `params` and profiles in `nextflow.config`.\n- **One container\u002Fconda env per process**; never rely on tools installed on the host.\n- **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.\n- **Right-size resources** with `process_low\u002Fmedium\u002Fhigh` labels and `errorStrategy 'retry'` with dynamic `task.attempt` scaling instead of one giant request.\n- **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`.\n\n## Reference Files\n\nRead the relevant file when you need depth — each is self-contained:\n\n- `references\u002Flanguage.md` — DSL2 language: processes, directives, channels, operators, workflows (`take`\u002F`emit`), modules, dynamic resources, error handling.\n- `references\u002Fconfiguration.md` — `nextflow.config`, scopes, `profiles`, `withName`\u002F`withLabel` selectors, executors (local\u002FSLURM\u002Fcloud), caching\u002F`-resume` internals, tracing\u002Freports, the `nextflow` CLI.\n- `references\u002Fcontainers.md` — Docker, Singularity\u002FApptainer, Podman, Conda, Wave containers; choosing and enabling engines; common gotchas.\n- `references\u002Frunning-pipelines.md` — finding\u002Frunning nf-core pipelines, samplesheets, params files, reference genomes (iGenomes), offline runs, institutional configs, Seqera Platform.\n- `references\u002Fnf-core-tools.md` — complete `nf-core` CLI reference (pipelines\u002Fmodules\u002Fsubworkflows), flags, and workflows.\n- `references\u002Fdeveloping.md` — authoring nf-core pipelines & modules: template layout, module `main.nf`\u002F`meta.yml`, meta maps, `ext.args`\u002F`modules.config`, subworkflows, resource labels, linting & Harshil alignment style.\n- `references\u002Ftesting.md` — nf-test for modules\u002Fsubworkflows\u002Fpipelines: test structure, assertions, snapshots, tags, running tests, CI.\n\nOfficial docs: Nextflow https:\u002F\u002Fwww.nextflow.io\u002Fdocs\u002Flatest\u002F · nf-core https:\u002F\u002Fnf-co.re\u002Fdocs\u002F · Training https:\u002F\u002Ftraining.nextflow.io\u002F\n\n## Agent operating procedure\n\n1. **Check the environment.** Confirm tool versions, the reference genome\u002Fannotation build and the input formats (FASTQ, BAM, VCF, h5ad).\n2. **Pin down the inputs.** Confirm formats, identifiers and parameters from the data or the user. Ask rather than guess any value that changes the result.\n3. **Run a small version first.** Run the pipeline on a small subset (one sample, one chromosome, a few thousand cells) first.\n4. **Execute the full task** using the instructions and references above.\n5. **Validate the result.** Check QC metrics, sample identities, genome build consistency and batch effects before interpreting results.\n6. **Report.** State what was run (versions, commands, parameters), what was checked, and what is still uncertain.\n\n| If this happens | Do this |\n|---|---|\n| Genome builds or identifiers do not match between inputs | Stop and harmonize (liftover, ID mapping) before continuing. |\n| A function, flag or endpoint in these instructions is missing in the installed version | Check the installed version's own documentation (`help()`, `--help`, official docs), adapt, and tell the user. Never invent an API. |\n| A required input, identifier or parameter is ambiguous | Ask the user, or state the assumption explicitly before running. |\n\n**Integrity rules**\n\n- Never fabricate results, parameters, identifiers, citations or statistics. If something cannot be run or verified, say so plainly.\n- Do not interpret biological significance beyond what the statistics support; report multiple-testing correction.\n- Treat version-specific details here as possibly outdated: confirm them against the official documentation for the installed version.\n- Ask before actions that cost money, consume shared GPUs or cloud quota, touch personal or patient data, or cannot be undone.\n\n## Related skills\n\n- `pacsomatic`: Operator toolkit for nf-core\u002Fpacsomatic matched tumor-normal workflows from BAM inputs.\n- `bulk-rnaseq`: End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp\u002FTrim Galore), alignment and quantificat…\n- `latchbio-integration`: Build, register, debug, and operate bioinformatics workflows on Latch using the Python SDK, CLI, Latch Data and Registry, Nextflow, Snakema…\n",{"name":5,"license":15,"metadata":51,"description":7},{"tags":52,"version":53,"category":54,"maintainer":55},"Nextflow, nf-core, bioinformatics pipelines, workflow management, genomics","1.2","life-sciences","Kalaris Labs","main","0da4485785ee599388900be50db1635489d53056",".agents\u002Fskills\u002Fkal-nextflow","https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6","https:\u002F\u002Fdisha6.6.thenitishkr.in\u002F","https:\u002F\u002Fgithub.com\u002FTashima-Tarsh","www.thenitishkr","thenitishkr | AI • Cyber-security • Research\r\n","2026-11-08 03:33:25",{"source":8,"skillName":5,"commands":66,"prompt":76,"zipAvailable":77},[67,70,73],{"tool":68,"command":69},"npx","npx skills add Tashima-Tarsh\u002FDisha6.6 --skill nextflow",{"tool":71,"command":72},"bunx","bunx skills add Tashima-Tarsh\u002FDisha6.6 --skill nextflow",{"tool":74,"command":75},"pnpm","pnpm dlx skills add Tashima-Tarsh\u002FDisha6.6 --skill nextflow","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fkal-nextflow\u002FSKILL.md",true,[79,85,89,93,97,101,105],{"path":80,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":83,"sourceHtmlUrl":84},"references\u002Fconfiguration.md","REFERENCE","参考文档",11318,"https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fkal-nextflow\u002Freferences\u002Fconfiguration.md",{"path":86,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":87,"sourceHtmlUrl":88},"references\u002Fcontainers.md",4598,"https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fkal-nextflow\u002Freferences\u002Fcontainers.md",{"path":90,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":91,"sourceHtmlUrl":92},"references\u002Fdeveloping.md",15378,"https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fkal-nextflow\u002Freferences\u002Fdeveloping.md",{"path":94,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":95,"sourceHtmlUrl":96},"references\u002Flanguage.md",15318,"https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fkal-nextflow\u002Freferences\u002Flanguage.md",{"path":98,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":99,"sourceHtmlUrl":100},"references\u002Fnf-core-tools.md",6357,"https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fkal-nextflow\u002Freferences\u002Fnf-core-tools.md",{"path":102,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":103,"sourceHtmlUrl":104},"references\u002Frunning-pipelines.md",6806,"https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fkal-nextflow\u002Freferences\u002Frunning-pipelines.md",{"path":106,"resourceType":81,"resourceTypeDesc":82,"sizeBytes":107,"sourceHtmlUrl":108},"references\u002Ftesting.md",6744,"https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fkal-nextflow\u002Freferences\u002Ftesting.md",[110,139,162,187,211,234],{"skillNo":111,"name":112,"nameZh":6,"description":113,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":114,"licenseFileUrl":6,"sourceHtmlUrl":115,"categories":116,"keywords":120,"publishedAt":46},"01M6QRD07D4TGNDK6VJ4EHF8BV","youtube-full","Use when the user needs YouTube transcripts, video search, channel browsing, playlist extraction, or content monitoring. Trigger phrases: 'get the transcript for', 'search YouTube for', 'what are the latest videos on', 'list this playlist', 'monitor this channel', or any request involving a YouTube URL, video ID, or @handle. Do NOT use for downloading video or audio files, YouTube engagement data (likes, comments), or private\u002Fage-restricted videos.","MIT","https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fyoutube-full\u002FSKILL.md",[117],{"categoryNo":118,"categoryName":119,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000016","图像与多媒体",[121,122,123,124,125,126,127,128,129,130,35,131,132,133,134,135,28,136,137,138],"youtube full","youtube","full","transcript","search","monitoring","data","Video","Audio","list","do","get","age","trigger","URL","browsing","request","youtube transcripts",{"skillNo":140,"name":141,"nameZh":6,"description":142,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":114,"licenseFileUrl":6,"sourceHtmlUrl":143,"categories":144,"keywords":145,"publishedAt":46},"01M6QRCJ3112VYPA97YG7KGMC2","x-twitter-growth","X\u002FTwitter growth engine for building audience, crafting viral content, and analyzing engagement. Use when the user wants to grow on X\u002FTwitter, write tweets or threads, analyze their X profile, research competitors on X, plan a posting strategy, or optimize engagement. Complements social-content (generic multi-platform) with X-specific depth: algorithm mechanics, thread engineering, reply strategy, profile optimization, and competitive intelligence via web search.","https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fx-twitter-growth\u002FSKILL.md",[],[146,147,148,149,125,150,151,152,153,154,155,156,38,157,37,158,159,160,161,28],"twitter","x twitter growth","growth","research","content","engineering","plan","web search","competitors","analyze","engine","strategy","platform","grow","posting","competitive",{"skillNo":163,"name":164,"nameZh":6,"description":165,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":114,"licenseFileUrl":6,"sourceHtmlUrl":166,"categories":167,"keywords":169,"publishedAt":46},"01M6QRBN3EHQNJY42RERP7A149","write-a-skill","Create new agent skills with proper structure, progressive disclosure, and bundled resources. Use when user wants to create, write, build, or author a new skill.","https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fwrite-a-skill\u002FSKILL.md",[168],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[170,38,171,172,173,174,175,176,37,177,178,56,179,180,181,182,183,184,185,186],"write a skill","github","create","https","productivity","matt pocock","direct","example","build","new skill","structure","new agent","resources","with","tree","progressive disclosure","author",{"skillNo":188,"name":189,"nameZh":6,"description":190,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":114,"licenseFileUrl":6,"sourceHtmlUrl":191,"categories":192,"keywords":193,"publishedAt":46},"01M6QRB6G8P33PNGAF9Y69EJ9T","wrap-up","Close out a launched Claude Managed Agent — recap every primitive the founder now owns, regenerate the single-file overview page, and suggest the next 1-2 upgrades. Use when the user says \"wrap up\", \"close this out\", \"what do I own now\", \"give me the summary\", \"recap the agent\", or when the orchestrator routes phase=wrap-up. primitives_inventory.py tables everything owned (agent, environment, session, memory, outcome, deployment); overview_page.py regenerates a self-contained .\u002Fmy-agent\u002Fagent-overview.html; upgrade_suggester.py ranks the next moves from recorded deferrals plus standing hardening steps. Companion to run-without-you; the last stop before phase=done.","https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fwrap-up\u002FSKILL.md",[],[194,195,196,197,198,42,199,200,201,37,202,131,203,204,205,206,207,208,209,210],"wrap up","up","wrap","gemini","deployment","file","hardening","closeout","stop","upgrade","founder","close","companion","you","tables","directions","phase",{"skillNo":212,"name":213,"nameZh":6,"description":214,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":114,"licenseFileUrl":6,"sourceHtmlUrl":215,"categories":216,"keywords":218,"publishedAt":46},"01M6QRA5AYC1RBFZ39GTWGS3N8","workflow-builder","Design and write deterministic multi-agent workflow scripts (.js files in .claude\u002Fworkflows\u002F) for Claude Code's Workflow tool. Use when a user wants to build, create, author, scaffold, or run a custom Claude Code workflow, orchestrate sub-agents (fan-out, pipeline, loop, judge-panel), or automate a repeatable multi-step task across fresh-context agents.","https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fworkflow-builder\u002FSKILL.md",[217],{"categoryNo":24,"categoryName":25,"taxonomyType":21,"taxonomyTypeDesc":22},[219,220,221,222,45,172,42,223,224,225,226,227,38,228,35,229,230,231,232,233],"workflow","workflow builder","builder","design","code","orchestrate","pipeline","loop","multi-agent","context","across","fresh","scripts","judge","claude code workflow",{"skillNo":235,"name":236,"nameZh":6,"description":237,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":114,"licenseFileUrl":6,"sourceHtmlUrl":238,"categories":239,"keywords":240,"publishedAt":46},"01M6QR7QMCZESKQA0ERW1E657M","weekly-review","Use when someone wants to run a weekly review, close open loops, audit stalled projects and commitments, get their system back to trusted, restart a lapsed review habit, or says \"\u002Fcs:weekly-review\". Walks David Allen's three-phase loop — GET CLEAR, GET CURRENT, GET CREATIVE — with deterministic scripts that inventory open loops, gate the checklist with named gaps, and score commitment health 0-100.","https:\u002F\u002Fgithub.com\u002FTashima-Tarsh\u002FDisha6.6\u002Fblob\u002Fmain\u002F.agents\u002Fskills\u002Fweekly-review\u002FSKILL.md",[],[241,242,243,244,245,246,247,248,249,226,250,251,252,253,254,255,132,256,257,210],"review","weekly review","weekly","deterministic scripts","reflect","feeds","inventory","open","team","projects","project-management","scanner","conversation","back","project","sprint","cadence"]