[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71GZYKVHVNJF1ZXAXKRM6ZQ":3,"skill-same:01M71GZYKVHVNJF1ZXAXKRM6ZQ":105},{"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":54,"commitSha":55,"skillDirectory":5,"forksCount":14,"repositoryHtmlUrl":56,"repositoryHomepageUrl":6,"ownerHtmlUrl":57,"ownerBlogUrl":58,"ownerDescription":59,"updatedAt":60,"install":61,"resources":74},"01M71GZYKVHVNJF1ZXAXKRM6ZQ","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.","agency-black\u002FSkills","agency-black","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F234862658?v=4","01M6HWVFPNGNR5N2CX9ECSAD57","agencia.black","01M719WF77BF3HN0N9FK1APEFY",0,"Apache-2.0","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fnextflow\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],"community","singularity","hpc","sure","scientific","linting","conda","end","operators","workflow","files","modules","work","configure","pipeline","batch","data pipelines","run","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: \"1.0\"\n  skill-author: K-Dense Inc.\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\npip 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","# 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\npip 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",{"name":5,"license":15,"metadata":51,"description":7},{"version":52,"skill-author":53},"1.0","K-Dense Inc.","main","681496e0662f4c45c4758fae9d4510ae87311bf2","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills","https:\u002F\u002Fgithub.com\u002Fagency-black","http:\u002F\u002Fwww.dogma.black","Las grandes ideas merecen una ejecución impecable. 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Use this skill whenever the user wants to add page transitions, animate route changes, create shared element animations, animate enter\u002Fexit of components, animate list reorder, implement directional (forward\u002Fback) navigation animations, or integrate view transitions in Next.js. Also use when the user mentions view transitions, `startViewTransition`, `ViewTransition`, transition types, or asks about animating between UI states in React without third-party animation libraries.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fvercel-react-view-transitions\u002FSKILL.md",[220],{"categoryNo":171,"categoryName":172,"taxonomyType":21,"taxonomyTypeDesc":22},[209,222,223,224,225,226,227,228,229,203,230,231,232,233,234,208,235,236,237,238],"vercel react view transitions","view","react view transitions","vercel","transitions","shared","back","Animation","types","states","element","implementing","when","api","route","create","libraries",{"skillNo":240,"name":241,"nameZh":6,"description":242,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":110,"licenseFileUrl":6,"sourceHtmlUrl":243,"categories":244,"keywords":246,"publishedAt":46},"01M71JS1WZ1J4F9YVC2203JBJW","vercel-react-native-skills","React Native and Expo best practices for building performant mobile apps. Use when building React Native components, optimizing list performance, implementing animations, or working with native modules. Triggers on tasks involving React Native, Expo, mobile performance, or native platform APIs.","https:\u002F\u002Fgithub.com\u002Fagency-black\u002FSkills\u002Fblob\u002Fmain\u002Fvercel-react-native-skills\u002FSKILL.md",[245],{"categoryNo":171,"categoryName":172,"taxonomyType":21,"taxonomyTypeDesc":22},[225,247,209,248,249,250,38,251,252,125,253,233,254,127,255,256,234,257,258,208],"vercel react native skills","react native","native","react native skills","platform","animations","performance","triggers","react native components","apps","best practices","tasks"]