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ngs-runtime-env

Check whether public NGS tools and packages already exist before downloading, installing, or running a sequencing pipeline.

60

Quality

76%

Does it follow best practices?

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tessl review fix ./plugins/ngs-analysis/skills/ngs-runtime-env/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

78%Weight 40%Scale 1-5

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

A highly actionable, executable skill body with a clear gated check-first workflow and disciplined, concrete language. Its weaknesses are structural: the reference-manager subcommand catalog is inlined where a one-level reference file would serve progressive disclosure, and there is no post-install verification step to close the feedback loop.

Suggestions

Move the ngs_reference_manager subcommand catalog (and per-subcommand output descriptions) into a references/ file (e.g., references/reference-manager.md) and link to it with a one-level, clearly signaled reference.

Add an explicit post-install validation step, e.g. 'After installing, re-run ngs_preflight.py --pipeline <name> to confirm all tools resolve' to create a validate→fix→retry loop.

Trim the exhaustive runner-type enumeration and duplicate command examples to reduce token cost without losing coverage.

DimensionReasoningScore

Conciseness

The body is information-dense throughout — no concept explanations Claude already knows, no padded prose — with concrete flags and outputs earning their tokens. Minor trimming is possible (e.g., the exhaustive runner enumeration 'bulk RNA-seq counts/QC, scRNA FASTQ-to-count, generic DNA, germline DNA, somatic DNA, UMI panel, ATAC, ChIP/CUT&RUN, amplicon, and shotgun' and ten near-identical ngs_reference_manager invocations), which fits 'Efficient; minor instances of over-explanation that could be trimmed' rather than the lean 5 or the padded 3.

4 / 5

Actionability

Every command is copy-paste executable from a stated working directory ('From the repo root'), covering the common cases: --list, --tool, --profile, --pipeline, install-plan output dirs, guarded install via --install-missing --yes, and the full reference-manager subcommand set. This matches 'Fully executable; copy-paste ready code or commands; specific examples cover the common cases'; nothing drops it to 4.

5 / 5

Workflow Clarity

The 'Existence Check Order' gives a clear numbered sequence (PATH check → Python imports → package managers → indexes → emit install plan → install only on request), and the existence checks themselves are validation. Gating is explicit ('Install only when explicitly requested by the user', the shell companion 'exits without installing unless NGS_RUN_INSTALL_COMMANDS=1'). It falls short of 5 because there is no post-install verification/re-check loop and no error-recovery guidance if a check fails — 'Clear sequence with most checkpoints present; minor validation gaps'.

4 / 5

Progressive Disclosure

The body is well-sectioned (Existence Check Order, Script, Install Strategy, Report) and flat, but no bundle files exist (references/, scripts/, assets/ are absent) and everything is inlined — notably the ten-command ngs_reference_manager catalog with per-subcommand output explanations, which is exactly the content that 'should be separate is inline'. This matches anchor 3; 4 would require the bulk of that detail to live in clearly signaled reference files.

3 / 5

Total

16

/

20

Passed

Description

61%Weight 40%Scale 1-5

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

A concise, domain-specific description with a clear 'what', but it lacks an explicit 'Use when...' trigger clause and natural synonym coverage (bioinformatics, fastq, conda), which limits completeness and trigger-term quality. The niche framing keeps conflict risk low.

Suggestions

Add an explicit trigger clause, e.g. 'Use when setting up or running an NGS/bioinformatics pipeline, or before installing sequencing tools.'

Include natural synonyms and artifacts users would mention: 'bioinformatics', 'conda/mamba environment', '.fastq/.bam files', 'FastQC', 'nf-core'.

List the concrete actions more comprehensively (e.g., 'checks executables, Python imports, and conda/pip packages; emits an install plan') to lift specificity.

DimensionReasoningScore

Specificity

The description names the domain (NGS tools and packages) and one concrete action — 'Check whether public NGS tools and packages already exist' — tied to context ('before downloading, installing, or running a sequencing pipeline'). This matches the anchor 'Names domain and 1-2 concrete actions, but not comprehensive'; a score of 4 would require several distinct listed actions (e.g., checking, planning installs, validating runtime readiness), and 2 would mean the action itself were generic.

3 / 5

Completeness

The 'what' is clear (existence check for NGS tools/packages), but there is no 'Use when...' clause or equivalent explicit trigger guidance; the 'when' is only weakly implied by 'before downloading, installing, or running a sequencing pipeline'. Per the rubric guideline, a missing 'Use when...' clause caps completeness at 3, and 4 would require an explicit 'when' statement.

3 / 5

Trigger Term Quality

Natural user phrasing is present: 'NGS', 'tools', 'packages', 'downloading', 'installing', 'sequencing pipeline'. It misses common variations users would say — 'bioinformatics', 'conda/mamba environment', '.fastq', 'FastQC' — so it fits 'Good keyword coverage; a few natural terms missing' rather than the comprehensive synonym/extension coverage of a 5.

4 / 5

Distinctiveness Conflict Risk

The NGS/sequencing-pipeline framing carves out a clear niche that most skills would not match ('public NGS tools and packages', 'sequencing pipeline'). It is 'mostly distinct' but the generic 'tools and packages... downloading, installing' phrasing leaves minor overlap risk with general package-management or environment-setup skills, keeping it just below the fully distinct 5 anchor.

4 / 5

Total

14

/

20

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

openai/plugins

Path

plugins/ngs-analysis/skills/ngs-runtime-env/SKILL.md

Reviewed

Table of Contents

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