Agent skill

Bio Workflow Management Cwl Workflows

by GPTomics in GPTomics/bioSkills

Authors portable, strongly-typed bioinformatics pipelines in the Common Workflow Language (CWL v1.2) as CommandLineTool/Workflow/ExpressionTool documents, validated with cwltool and run at scale on…

MITAuto-check passedResearch & Science

Install Bio Workflow Management Cwl Workflows

skills CLI
$ npx skills add GPTomics/bioSkills --skill bio-workflow-management-cwl-workflows -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install GPTomics/bioSkills bio-workflow-management-cwl-workflows --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/workflow-management/cwl-workflows .claude/skills/bio-workflow-management-cwl-workflows && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
bio-workflow-management-cwl-workflows
GitHub stars
1.2k
Used in
1 other repo
Token cost
~4.6k tokens
SKILL.md length
1,948 words
Files
3
Skills in repo
559
Repo updated
First seen
Licence
MIT

At a glance

Authors portable, strongly-typed bioinformatics pipelines in the Common Workflow Language (CWL v1.2) as CommandLineTool/Workflow/ExpressionTool documents, validated with cwltool and run at scale on…

  • Deciding CWL (portability/provenance/regulated) vs Nextflow/WDL/Snakemake
  • SKILL.md covers Version Compatibility, The governing principle: CWL…, Decision: choose CWL vs the… and Decision: which runner, plus 12 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Declaring secondaryFiles for indexed companions (.bai/.fai/.dict/.tbi and the caret rule)

What it does

Bio Workflow Management Cwl Workflows is an agent skill from GPTomics/bioSkills. Authors portable, strongly-typed bioinformatics pipelines in the Common Workflow Language (CWL v1.2) as CommandLineTool/Workflow/ExpressionTool documents, validated with cwltool and run at scale on Toil/Arvados/Calrissian. Use when deciding CWL (portability/provenance/regulated) vs Nextflow/WDL/Snakemake; declaring secondaryFiles for indexed companions (.bai/.fai/.dict/.tbi and the caret rule); putting resources/containers under requirements (must-hold) vs hints (advisory) to avoid silent OOM; choosing…

Its SKILL.md is about 4.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `usage-guide.md`).

It sits in Research & Science, covering Reproducible research, Site reliability engineering and Bioinformatics. It works with Nextflow and JavaScript. The repository describes itself as: a set of SKILLS.md for doing bioinformatics with agents like claude code. The licence is MIT.

When your agent uses it

  • Deciding CWL (portability/provenance/regulated) vs Nextflow/WDL/Snakemake
  • Declaring secondaryFiles for indexed companions (.bai/.fai/.dict/.tbi and the caret rule)
  • Putting resources/containers under requirements (must-hold) vs hints (advisory) to avoid silent OOM
  • Choosing scatterMethod (dotproduct vs flat/nestedcrossproduct)

Example prompts

  • “Use the bio-workflow-management-cwl-workflows skill to author portable, strongly-typed bioinformatics pipelines in the Common Workflow Language (CWL…”
  • “/bio-workflow-management-cwl-workflows”

Requirements

  • Python 3
  • Docker

What it can do on your machine

Read from SKILL.md and the folder at commit d91ed3d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are yaml and bash).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Bio Workflow Management Cwl Workflows loads about 4.6k tokens when it runs. Until then it costs about 195 tokens; SKILL.md has 1,948 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~195
When it runs · the whole SKILL.md, loaded when a task matches
~4.6k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from GPTomics/bioSkills at commit d91ed3d, republished under its MIT licence (© GPTomics). 1,948 words, ~4,601 tokens.

Download SKILL.mdSave it as .claude/skills/bio-workflow-management-cwl-workflows/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
bio-workflow-management-cwl-workflows
description
Authors portable, strongly-typed bioinformatics pipelines in the Common Workflow Language (CWL v1.2) as CommandLineTool/Workflow/ExpressionTool documents, validated with cwltool and run at scale on Toil/Arvados/Calrissian. Use when deciding CWL (portability/provenance/regulated) vs Nextflow/WDL/Snakemake; declaring secondaryFiles for indexed companions (.bai/.fai/.dict/.tbi and the caret rule); putting resources/containers under requirements (must-hold) vs hints (advisory) to avoid silent OOM; choosing scatterMethod (dotproduct vs flat_/nested_crossproduct); preferring $(...) parameter refs over ${...} JavaScript for portability; pinning DockerRequirement images; or emitting a CWLProv provenance object for audited/clinical settings.
tool_type
cli
primary_tool
cwltool

Version Compatibility

Reference examples tested with: cwltool 3.1+, CWL spec v1.2, Docker 24+ (or Singularity/Apptainer 3.8+)

Before using code patterns, verify installed versions match. If versions differ:

  • CLI: <tool> --version then <tool> --help to confirm flags

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Note: target cwlVersion: v1.2 for genomics (the record-form secondaryFiles with required: needs it). cwltool is the REFERENCE runner - correct, local, single-node, deliberately slow - NOT the spec; run Toil/Arvados/Calrissian at scale. In v1.2, ExpressionTool outputs are NOT type-checked (a known reference-impl gap, fix planned for v1.3), so do not lean on ExpressionTool for type safety.

CWL Workflows

"Write a portable pipeline that runs the same everywhere and proves what it ran" -> Describe each tool and their wiring as strongly-typed, machine-checkable CWL documents that any conforming runner honors identically, validate the contract before any compute, then execute locally (cwltool) or at scale (Toil/Arvados/Calrissian).

  • CLI: cwltool --validate wf.cwl, cwltool wf.cwl job.yml, cwltool --provenance ro/ wf.cwl job.yml
  • YAML: class: CommandLineTool (wrap a tool) and class: Workflow (wire tools) at cwlVersion: v1.2

The governing principle: CWL is a SPECIFICATION, not an engine

CWL deliberately splits the workflow DESCRIPTION (a portable, declarative, strongly-typed YAML/JSON document) from its EXECUTION (performed by any conforming runner). Nextflow and Snakemake are engines that happen to have a DSL; WDL is a language with a dominant engine (Cromwell). CWL alone is a community-governed open standard with multiple independent implementations and a formal conformance test suite (Crusoe 2022 Commun ACM 65(6):54-63). The whole value proposition - portability, auditability, vendor-neutrality, provenance, regulatory fit - is a consequence of "spec not engine." The correct frame: the author writes a portable, machine-checkable CONTRACT for a computation that any conforming platform must honor identically. That contract is why CWL is the most VERBOSE and most EXPLICIT of the four systems - the verbosity buys static analyzability and portability.

The most common conceptual error is conflating CWL with cwltool. cwltool is the reference implementation: correct, single-node, and slow by design (it prioritizes spec-conformance over speed). "CWL is slow" or "CWL can't scale" almost always means "I ran cwltool" - at scale the same unchanged document runs on Toil (HPC/cloud batch), Arvados (clinical/enterprise data management), or Calrissian (Kubernetes). Never equate a runner's limits with the spec's.

Adopting CWL buys reproducible workflow LOGIC and nothing else automatically. A clean typed DAG over unpinned tools is NOT reproducible - pin the software environment (containers by digest, not a moving :latest), the reference data and seeds, and control arch/thread/locale leaks separately. The type system closes the wiring-error layer; the author still owns the rest.

Decision: choose CWL vs the other engines

DimensionCWLNextflowWDLSnakemake
Natureopen SPEC, many enginesengine + Groovy DSLlanguage + Cromwell/miniwdlengine + Python DSL
Typingstrong static (File/Dir/record/enum/optional)dynamicmoderateweak (paths/strings)
Index companionssecondaryFiles = File type propertymanual channel/tuple wiringmanual per-inputmanual
ProvenanceCWLProv RO out of the boxreport/trace/DAGvia platformreport/plugins
VerbosityHIGHEST (deliberate)tersemoderatemoderate
New-author mindshareDECLININGASCENDANT (nf-core)strong on Terrastrong in academia
Sweet spotmulti-platform, provenance-critical, regulated/clinical, standards-drivenfast authoring, curated catalogTerra/GATK ecosystemsingle-lab Python/HPC

Choose CWL when vendor-neutral portability across multiple platforms, a standardized provenance artifact for a regulated/audited setting, static type-checking before compute, or publishing to a multi-runner registry (Dockstore) drives the decision. Be honest about mindshare: for NEW pipeline authoring CWL has been losing ground to Nextflow/nf-core and WDL/Terra for years (they win on authoring speed and community momentum). CWL retains and deepens its hold where the SPEC is the point - not as a neutral default. Prefer Nextflow/WDL when authoring speed, an existing curated catalog (nf-core), or a specific hosted platform (Terra) dominates.

Decision: which runner

EngineForRuntime modelNotes
cwltoolauthoring, --validate, --pack, --provenance, CI, local devlocal, single-nodethe conformance yardstick; slow by design - do NOT read its limits as CWL's
ToilHPC and cloud batch scalePython; Slurm/Kubernetes/AWS/Grid Enginetoil-cwl-runner; the workhorse for large CWL
Arvadosenterprise/clinical data management + executioncluster + content-addressed storagearvados-cwl-runner; strong data provenance; regulated settings
CalrissianCWL on Kubernetesone k8s pod per stepneeds ReadWriteMany volumes; cloud-native parallelism
Cromwellprimarily WDL, PARTIAL CWLJVMruns a subset only; do not rely on it for full CWL conformance

Decision: requirements vs hints (get this wrong and jobs silently OOM)

requirements MUST be satisfied - if the runner cannot honor one, execution FAILS loudly (correctly). hints are advisory: the runner MAY honor or ignore them without error. The canonical failure is putting ResourceRequirement: {ramMin: 32000} under hints on a memory-hungry step - a runner is free to ignore a hint and schedule it on a small node, giving intermittent OOM kills. Anything whose absence would corrupt results or crash (the container, minimum RAM/cores, a required input layout, an env var a tool depends on) goes under requirements. Both inherit Workflow -> step -> tool with the INNERMOST declaration winning, so set a default DockerRequirement/ResourceRequirement at workflow scope and override per-step where a tool needs a different image or more RAM. A surprising container at a step is usually a forgotten override.

Decision: scatterMethod

scatter runs a step once per array element; when scattering over MULTIPLE inputs, scatterMethod decides how they combine. This is the most misunderstood CWL construct.

scatterMethodCombines byJobsOutput shapeUse when
dotproductposition-aligned zipN (arrays MUST be equal length)flat array of Npaired arrays that correspond 1:1 (R1[i] with R2[i])
flat_crossproductevery combinationN x MFLAT array of N x Mall pairs, want a flat result list
nested_crossproductevery combinationN x MNESTED array (N of M)all pairs, preserve the 2-D grid

dotproduct requires equal-length arrays (unequal is an error, not truncation). The two cross-products run the SAME N x M jobs and differ only in output nesting - choosing flat_ vs nested_ wrong gives the right computations with a mis-shaped output that then mis-wires a downstream File[] step. ScatterFeatureRequirement must be declared regardless of scatterMethod.

CommandLineTool: wrap one tool

A CommandLineTool binds typed inputs to the command line (inputBinding) and captures outputs (outputBinding.glob or stdout). Tool outputs use outputBinding; workflow outputs use outputSource - mixing them is a validation error.

yaml
cwlVersion: v1.2
class: CommandLineTool
baseCommand: [bwa, mem]
requirements:
  DockerRequirement:
    dockerPull: quay.io/biocontainers/bwa:0.7.17--he4a0461_11   # digest-pin in production; :latest breaks reproducibility
  ResourceRequirement:            # under requirements: must hold, or the runner fails loudly (a hint could be ignored -> OOM)
    coresMin: 8
    ramMin: 16000                 # MB; bwa-mem index residency + reads, empirical floor for a human genome
inputs:
  reference:
    type: File
    secondaryFiles:               # the .amb/.ann/.bwt/.pac/.sa BWA index files are STAGED next to the fasta
      [.amb, .ann, .bwt, .pac, .sa]
    inputBinding: {position: 2}
  reads_1: {type: File, inputBinding: {position: 3}}
  reads_2: {type: File?, inputBinding: {position: 4}}   # File? is optional: [null, File]
  threads: {type: int, default: 8, inputBinding: {prefix: -t, position: 1}}
stdout: aligned.sam
outputs:
  sam: {type: stdout}

Workflow: wire tools by explicit typed connections

CWL is PULL/goal-oriented and fully declarative: dataflow is wired explicitly through source/outputSource, never through implicit channels (Nextflow) or filename wildcards (Snakemake). --validate type-checks every connection statically, before a byte of data moves.

yaml
cwlVersion: v1.2
class: Workflow
requirements:
  ScatterFeatureRequirement: {}
inputs:
  fastq_1: File
  fastq_2: File
  salmon_index: Directory
outputs:
  quant_results:
    type: Directory
    outputSource: salmon/quant_dir     # workflow output wires with outputSource (NOT outputBinding)
steps:
  fastp:
    run: fastp.cwl
    in: {reads_1: fastq_1, reads_2: fastq_2}
    out: [trimmed_1, trimmed_2, json_report]
  salmon:
    run: salmon_quant.cwl
    in: {index: salmon_index, reads_1: fastp/trimmed_1, reads_2: fastp/trimmed_2}   # source: other_step/output
    out: [quant_dir]

secondaryFiles: index and companion files as a type property

Genomics tools demand companion files that must sit next to the primary with a derived name: .bam needs .bai, .fasta needs .fai and .dict, .vcf.gz needs .tbi. CWL makes the companion a PROPERTY of the File type, so every conforming runner is OBLIGATED to co-stage them - the other engines leave this to hand-wiring. This is the single most genomics-relevant CWL feature and the strongest reason to target v1.2.

yaml
inputs:
  bam:
    type: File
    secondaryFiles: [.bai]         # append: sample.bam -> sample.bam.bai staged alongside
  reference:
    type: File
    secondaryFiles:                # v1.2 record form makes required-ness explicit
      - {pattern: .fai, required: true}
      - {pattern: ^.dict, required: false}   # caret ^ STRIPS one extension: genome.fasta -> genome.dict (NOT genome.fasta.dict)

The caret ^ removes one extension from the basename before appending; each leading ^ strips one more - the classic .dict gotcha. In v1.0/v1.1 a bare string pattern is required-by-default; only the v1.2 record {pattern, required} form can mark an index optional (a .tbi that may be absent). secondaryFiles are declared on OUTPUT File parameters too, so a produced BAM carries its .bai to the next step; on inputs required defaults true, on outputs the index is collected if present.

Show full SKILL.md (730 more words)Show less

Expressions: $(...) is portable, ${...} is a portability debt

Parameter references $(...) are a restricted, safe subset - property/index access into inputs, self, runtime (e.g. $(inputs.reads.nameroot), $(runtime.outdir)). They need NO JavaScript engine, are statically analyzable, and are portable - prefer them. Full JavaScript ${ return ...; } runs only when InlineJavascriptRequirement is present; it is powerful but (a) needs a node engine wherever the workflow runs, (b) is opaque to static analysis, (c) is the leading cause of "works on my runner, breaks on theirs." Reach for ${...} only when a parameter reference genuinely cannot express the need, and treat every InlineJavascriptRequirement as a portability debt taken on knowingly. valueFrom transforms a step input before it reaches the tool (needs StepInputExpressionRequirement for expressions at step scope).

Portability leaks: "run anywhere" is real but DISCIPLINED

The promise is genuine for disciplined CWL, but it leaks - name the leaks. InlineJavascriptRequirement needs a JS engine (node). DockerRequirement carries arch/registry assumptions (an amd64-only image fails on arm64 Apple Silicon/Graviton; a private-registry image needs credentials the target may lack; :latest is not reproducible). Engine-specific extensions under custom namespaces (cwltool:, arv:) are portable only among runners that understand them - they live under hints so a naive runner can ignore them, but a workflow that DEPENDS on their behavior has forfeited portability. Conformance is graded (a coverage percentage per implementation), not binary - "valid CWL" does not guarantee "runs identically on engine X." The disciplined recipe: target v1.2; containerize every tool with a digest-pinned multi-arch image; minimize ${...} in favor of $(...); keep cwltool:/arv: items under hints and never depend on them for correctness; in the input (job) object prefer location: URIs over a local path: (a path: binds the job to one machine's filesystem); validate, then exercise the real target engine before trusting portability.

Provenance: CWL's high ground for regulated/clinical settings

cwltool --provenance ro/ wf.cwl job.yml produces a CWLProv Research Object (a W3C PROV + RO-Crate/BagIt bundle) capturing the workflow, the exact input object, all outputs, intermediates, container images, and the enactment trace (Khan 2019 GigaScience 8(11):giz095). No other mainstream system ships a standardized retrospective-provenance artifact out of the box - this is the concrete reason CWL wins in regulated/audited genomics: hand an auditor one object that answers "exactly what ran, on what inputs, in what containers, producing what outputs." CWL is also a first-class GA4GH citizen: TRS (Tool Registry Service, implemented by Dockstore) standardizes discovery, WES standardizes cross-platform execution - the strongest reproducibility+portability+provenance story of the four systems.

Run commands

bash
cwltool --validate wf.cwl                     # static type-check the contract; no compute
cwltool wf.cwl job.yml                         # run locally (reference runner)
cwltool --singularity wf.cwl job.yml           # swap container runtime (Apptainer is Singularity-compatible)
cwltool --pack wf.cwl > packed.cwl             # bundle a multi-file workflow into one shareable JSON
cwltool --provenance ro/ wf.cwl job.yml        # emit a CWLProv Research Object
toil-cwl-runner --batchSystem slurm wf.cwl job.yml   # same document, at HPC scale

Common Errors

SymptomCauseFix
"CWL is slow / can't scale"ran cwltool (reference runner, single-node, slow by design)run the same document on Toil/Arvados/Calrissian; do not equate runner limits with the spec
"index not found" at runtime (e.g. no .bai/.fai)secondaryFiles not declared, so the runner staged the primary but not its indexdeclare secondaryFiles on the indexed File input (and output)
genome.fasta.dict produced instead of genome.dictforgot the caret; .dict appends, ^.dict strips one extensionuse ^.dict (each ^ strips one extension)
Intermittent OOM / undersized node on a heavy stepResourceRequirement placed under hints (advisory, may be ignored)move anything that MUST hold under requirements
Validation error on a workflow outputused outputBinding.glob on a workflow outputworkflow outputs wire via outputSource: step/out; only tool outputs use outputBinding
Scatter runs but produces N x M or wrong-shaped outputwrong scatterMethod (dotproduct vs flat_/nested_crossproduct)pick deliberately: dotproduct=zip, flat_/nested_=all pairs (flat vs nested output)
Works on cwltool, fails/differs on another engine${...} JS or cwltool:/arv: extension the target lacks; graded conformanceprefer $(...); keep engine extensions in hints; test the real target
"ScatterFeatureRequirement not specified"used scatter: without the feature flagadd requirements: [ScatterFeatureRequirement]
Non-reproducible result across timemutable :latest container tagpin DockerRequirement by @sha256: digest
  • workflow-management/wdl-workflows - WDL/Cromwell alternative for the Terra/GATK ecosystem
  • workflow-management/nextflow-pipelines - reactive-dataflow alternative with the nf-core catalog
  • workflow-management/snakemake-workflows - Python/file-pattern alternative for single-lab HPC
  • workflows/fastq-to-variants - an end-to-end variant-calling pipeline these engines orchestrate

References

  • Crusoe MR, Abeln S, Iosup A, et al. 2022. Methods Included: Standardizing Computational Reuse and Portability with the Common Workflow Language. Commun ACM 65(6):54-63. DOI 10.1145/3486897.
  • Amstutz P, Crusoe MR, Tijanic N, et al. 2016. Common Workflow Language, v1.0. figshare. DOI 10.6084/m9.figshare.3115156.v2.
  • Khan FZ, Soiland-Reyes S, Sinnott RO, Lonie A, Goble C, Crusoe MR. 2019. Sharing interoperable workflow provenance: a review of best practices and their practical application in CWLProv. GigaScience 8(11):giz095. DOI 10.1093/gigascience/giz095.
  • Wratten L, Wilm A, Göke J. 2021. Reproducible, scalable, and shareable analysis pipelines with bioinformatics workflow managers. Nat Methods 18:1161-1168. DOI 10.1038/s41592-021-01254-9.

© GPTomics, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files in workflow-management/cwl-workflows of GPTomics/bioSkills.

  • SKILL.md
  • examples/rnaseq.cwl
  • usage-guide.md

Open the folder on GitHubat commit d91ed3d

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in GPTomics/bioSkills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Questions about Bio Workflow Management Cwl Workflows

What does Bio Workflow Management Cwl Workflows do?

Authors portable, strongly-typed bioinformatics pipelines in the Common Workflow Language (CWL v1.2) as CommandLineTool/Workflow/ExpressionTool documents, validated with cwltool and run at scale on…. Bio Workflow Management Cwl Workflows is an agent skill from GPTomics/bioSkills.2) as CommandLineTool/Workflow/ExpressionTool documents, validated with cwltool and run at scale on Toil/Arvados/Calrissian.

When should I use Bio Workflow Management Cwl Workflows?

Bio Workflow Management Cwl Workflows fits situations like: deciding CWL (portability/provenance/regulated) vs Nextflow/WDL/Snakemake; declaring secondaryFiles for indexed companions (.bai/.fai/.dict/.tbi and the caret rule); putting resources/containers under requirements (must-hold) vs hints (advisory) to avoid silent OOM; choosing scatterMethod (dotproduct vs flat/nestedcrossproduct).

How do I install Bio Workflow Management Cwl Workflows in Claude Code?

Run `npx skills add GPTomics/bioSkills --skill bio-workflow-management-cwl-workflows -a claude-code`. Or copy the skill folder (workflow-management/cwl-workflows in GPTomics/bioSkills) into .claude/skills/bio-workflow-management-cwl-workflows in your project. Claude Code loads it when a task matches its description.

How do I install Bio Workflow Management Cwl Workflows in Codex?

Run `npx skills add GPTomics/bioSkills --skill bio-workflow-management-cwl-workflows -a codex`. Or copy the skill folder (workflow-management/cwl-workflows in GPTomics/bioSkills) into .agents/skills/bio-workflow-management-cwl-workflows in your project. Codex loads it when a task matches its description.

Can I use Bio Workflow Management Cwl Workflows in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add GPTomics/bioSkills --skill bio-workflow-management-cwl-workflows -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bio-workflow-management-cwl-workflows, .gemini/skills/bio-workflow-management-cwl-workflows, .github/skills/bio-workflow-management-cwl-workflows and .opencode/skills/bio-workflow-management-cwl-workflows in your project.

What does Bio Workflow Management Cwl Workflows need to run?

SKILL.md names no scripts, command-line tools or credentials: Bio Workflow Management Cwl Workflows is instructions for the agent only. Our summary lists: Python 3; Docker.

Does Bio Workflow Management Cwl Workflows access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Bio Workflow Management Cwl Workflows safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Bio Workflow Management Cwl Workflows use?

Bio Workflow Management Cwl Workflows is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Bio Workflow Management Cwl Workflows use?

About 4.6k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Bio Workflow Management Cwl Workflows?

Skills that share tags, products or a category with Bio Workflow Management Cwl Workflows: LaminDB Biological Data Management (davila7/claude-code-templates, 32k stars), Latchbio Integration (davila7/claude-code-templates, 32k stars), Latchbio Integration (K-Dense-AI/scientific-agent-skills, 48k stars) and Pacsomatic (K-Dense-AI/scientific-agent-skills, 48k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bio Workflow Management Cwl Workflows?

GPTomics (a GitHub organization) maintains it in GPTomics/bioSkills, which has 1,217 GitHub stars. The repository holds 559 skills in this directory. The repository was last updated on August 15, 2026.

Source: GPTomics/bioSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.