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nextflow

Build, run, and debug Nextflow data pipelines and nf-core workflows end to end. Use whenever the user mentions Nextflow, nf-core, .nf files, nextflow.config, DSL2, processes/channels/operators, samplesheets, or wants to run a community pipeline (e.g. nf-core/rnaseq, nf-core/sarek), write or test a module/subworkflow with nf-test, configure executors/containers (Docker, Singularity/Apptainer, Conda, Wave), scale a workflow to HPC/SLURM or cloud (AWS Batch, Google Batch, Azure, Kubernetes), or debug a failed/-resume run. Make sure to use this skill for any reproducible scientific/bioinformatics workflow work even if the user does not say the word "Nextflow", and for authoring nf-core-compliant pipelines, modules, configs, and linting.

70

Quality

86%

Does it follow best practices?

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SecuritybySnyk

Medium

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Content

72%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable with strong progressive disclosure and executable examples throughout. It is slightly held back by some conceptual re-explanation in the Overview/Core Concepts and by the absence of explicit validation feedback loops for destructive operations like `nextflow clean`.

Suggestions

Trim the Overview 'Dataflow programming / Write once run anywhere / Reproducibility' bullets and the Core Concepts glossary to the non-obvious specifics, moving definitional material to references/language.md to improve conciseness.

Add an explicit validate→fix→retry checkpoint around destructive/batch operations (e.g. a 'before running `nextflow clean -f`, confirm the run with `nextflow log`' step) to lift workflow clarity.

Consider condensing the two CLI command tables or moving exhaustive flag lists into the corresponding reference files, keeping only the highest-value commands inline.

DimensionReasoningScore

Conciseness

Mostly efficient and assumes Claude's competence, but the Overview ('Dataflow programming', 'Write once, run anywhere') and the Core Concepts glossary re-explain concepts Claude largely already knows, and the two CLI tables are lengthy; this matches 'mostly efficient but includes some unnecessary explanation' rather than the fully-lean level-3 anchor.

2 / 3

Actionability

Provides copy-paste-ready, executable guidance — install commands, a complete working SAYHELLO process, concrete `nextflow run` invocations with pinned flags, and specific CLI commands — matching the level-3 'fully executable, copy-paste ready' anchor rather than the pseudocode/incomplete level-2 anchor.

3 / 3

Workflow Clarity

Sequencing is clear (the 'Two Modes of Work' routing table and 'test first → real run' narrative), but risky/destructive operations like `nextflow clean -f` lack an explicit validate→fix→retry feedback loop, so per the rubric's feedback-loop rule workflow clarity is capped at the level-2 'sequence present but checkpoints implicit' anchor.

2 / 3

Progressive Disclosure

SKILL.md acts as a concise overview with seven verified, clearly-signaled, one-level-deep reference files, each described inline and in the Reference Files section with a routing table — matching the level-3 'clear overview with well-signaled one-level-deep references' anchor rather than the less-organized level-2 anchor.

3 / 3

Total

10

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12

Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is excellent: third-person, highly specific, with explicit 'Use whenever...' triggers and broad natural keyword coverage. It clearly communicates both capability and invocation conditions with minimal risk of conflicting with other skills.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Build, run, and debug', 'write or test a module/subworkflow with nf-test', 'configure executors/containers', 'scale a workflow to HPC/SLURM or cloud', and 'authoring nf-core-compliant pipelines, modules, configs, and linting' — matching the 'multiple specific concrete actions' anchor rather than the partial level-2 anchor.

3 / 3

Completeness

Explicitly answers both what (build/run/debug/author pipelines) and when via the 'Use whenever the user mentions...' trigger clause, matching the level-3 anchor; it is not level 2 because the 'when' is explicit rather than merely implied.

3 / 3

Trigger Term Quality

Covers natural terms users would say — 'Nextflow, nf-core, .nf files, nextflow.config, DSL2, processes/channels/operators, samplesheets' plus concrete pipeline names — with good coverage of variations, matching the level-3 anchor and exceeding the level-2 'some keywords' bar.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche (Nextflow/nf-core bioinformatics workflows) with distinct domain-specific triggers unlikely to fire for unrelated skills, matching the level-3 'clear niche with distinct triggers' anchor rather than the overlapping level-2 anchor.

3 / 3

Total

12

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
K-Dense-AI/scientific-agent-skills
Reviewed

Table of Contents

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