pydeseq2

Differential gene expression analysis (Python DESeq2). Identify DE genes from bulk RNA-seq counts, Wald tests, FDR correction, volcano/MA plots, for RNA-seq analysis.

Quality

73%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./skills/bio/pydeseq2/SKILL.md

Quality

Content

65%

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

A highly actionable, well-structured guide with comprehensive executable examples, weakened by verbosity/repetition, missing validation checkpoints in the batch workflow, and bundle references that point to non-existent files. Tightening the body and actually shipping the referenced files would materially improve it.

Suggestions

Add explicit validation checkpoints to the workflow (e.g., after data loading verify counts shape and sample-name alignment, and after deseq2() verify size factors/dispersions before testing), especially in the Multiple Comparisons batch loop.

Either create the referenced references/api_reference.md, references/workflow_guide.md, and scripts/run_deseq2_analysis.py files, or remove the references — broken paths undermine progressive disclosure.

De-duplicate the body: the Quick Start workflow, Two-Group Comparison pattern, and Core Workflow Steps overlap heavily; consolidate to reduce repetition and token cost.

Dimension	Reasoning	Score
Conciseness	Mostly efficient executable code, but the ~550-line body repeats itself — the Quick Start workflow reappears nearly verbatim in the Two-Group Comparison pattern and is restated across Core Workflow Steps — and could be tightened; not a score-1 wall of conceptual filler, but not maximally lean either.	2 / 3
Actionability	Provides fully executable, copy-paste ready Python and bash commands with concrete parameter values, result-DataFrame column references, and a runnable CLI script invocation.	3 / 3
Workflow Clarity	Steps 1–6 are clearly sequenced and troubleshooting gives error recovery, but there are no explicit validation checkpoints between steps, and the Multiple Comparisons batch loop performs destructive/batch analysis with no verification — capping workflow clarity at 2 per the rubric.	2 / 3
Progressive Disclosure	Sections are clearly organized and references are explicitly signaled (with Read instructions), but the referenced files (references/api_reference.md, references/workflow_guide.md, scripts/run_deseq2_analysis.py) do not exist in the bundle, and content that should live in those separate files is instead inlined as a monolithic body.	2 / 3
	Total	9 / 12 Passed

Description

82%

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 specific, third-person description with strong trigger terms and a distinct niche, held back only by an implied rather than explicit 'Use when...' trigger clause. Adding an explicit usage trigger would raise the completeness dimension.

Suggestions

Add an explicit 'Use when...' clause naming concrete user triggers (e.g., 'Use when analyzing bulk RNA-seq count data for differential expression, converting R DESeq2 workflows to Python, or when users mention DESeq2/PyDESeq2').

The trailing 'for RNA-seq analysis' is generic; replace it with the specific trigger conditions already enumerated in the body's 'When to Use This Skill' section.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — "Identify DE genes from bulk RNA-seq counts", "Wald tests", "FDR correction", "volcano/MA plots" — matching the 'lists multiple specific concrete actions' anchor.	3 / 3
Completeness	Clearly answers 'what' but 'when' is only implied by the trailing "for RNA-seq analysis" rather than an explicit 'Use when...' clause, which caps completeness at 2 per the judging guidelines.	2 / 3
Trigger Term Quality	Includes natural terms users would say — "differential gene expression", "DESeq2", "RNA-seq", "DE genes" — giving good coverage of common variations.	3 / 3
Distinctiveness Conflict Risk	A clear DESeq2/PyDESeq2 differential-expression niche with distinct triggers, unlikely to conflict with other skills.	3 / 3
	Total	11 / 12 Passed

Validation

81%

Warnings & errors only

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

Validation — 13 / 16 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (559 lines); consider splitting into references/ and linking	Warning
metadata_version	'metadata.version' is missing	Warning
referenced_paths_exist	Referenced path issues: 8 missing	Warning

	Total	13 / 16 Passed

Repository: wu-yc/LabClaw
Path: skills/bio/pydeseq2/SKILL.md
Commit: df37802

Reviewed: about 1 hour ago

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