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%

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tessl review fix ./backend/cli/skills/biology/pydeseq2/SKILL.md

Quality

Content

75%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.

The body is highly actionable with executable code and a clear sequenced workflow supported by verification and troubleshooting sections, but it is longer than necessary due to redundant recap sections and inlined content that duplicates the bundled reference files.

Suggestions

Remove or drastically trim the 'Key Reminders' section since every point is already made in the workflow steps above, removing pure padding.

Move the full visualization code and/or troubleshooting detail into the workflow guide reference, keeping only a minimal example inline with a clear pointer.

Consolidate 'Common Analysis Patterns' (two-group, multi-factor, batch, continuous) into a single compact table or one parameterized example rather than four near-duplicate fit-and-summarize blocks.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with abundant actionable code, but the 'Key Reminders' section repeats points already covered (data orientation, filtering, design order, LFC timing, contrast format) and 'Common Analysis Patterns' re-runs the basic fit-and-summarize workflow several times with minor variations.	3 / 5
Actionability	Fully executable, copy-paste-ready code throughout — Quick Start, all six core steps, CLI script invocations, visualization, and troubleshooting — with concrete tips (contrast format, result columns, shrinkage timing) covering the common cases.	5 / 5
Workflow Clarity	A clearly numbered six-step sequence with supporting verification patterns (size-factor, dispersion, and p-value distribution checks in Quality Metrics) and a troubleshooting feedback section; minor gap is the lack of inline 'validate before proceeding' gates in the main linear workflow.	4 / 5
Progressive Disclosure	Good structure with well-signaled one-level-deep references ('API Reference (references/api_reference.md): Use when...', 'Workflow Guide (references/workflow_guide.md): Use when...') and a real script, but a large volume of inlined content (full visualization code, troubleshooting, common patterns) overlaps material that the workflow guide already covers.	4 / 5
	Total	16 / 20 Passed

Description

71%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.

The description is specific and action-rich with good trigger keywords, but it lacks an explicit 'Use when...' trigger clause, leaving the 'when' only weakly implied and capping completeness at 3.

Suggestions

Add an explicit 'Use when...' clause naming concrete triggers, e.g. 'Use when analyzing bulk RNA-seq counts, comparing conditions, or when the user mentions DESeq2, differential expression, or RNA-seq.'

Include common synonyms and file extensions (e.g. 'differential expression', '.csv count matrices') to lift trigger term coverage to comprehensive.

Drop the redundant trailing 'for RNA-seq analysis' once a 'Use when' clause is added, to avoid padding.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'Identify DE genes from bulk RNA-seq counts', 'Wald tests', 'FDR correction', 'volcano/MA plots' — giving comprehensive coverage of the domain's capabilities.	5 / 5
Completeness	The 'what' is clear (DE analysis with Wald tests, FDR, plots) but the 'when' is only weakly implied by the trailing 'for RNA-seq analysis'; there is no 'Use when...' clause, capping completeness at 3 per the rubric guideline.	3 / 5
Trigger Term Quality	Good natural keyword coverage ('RNA-seq', 'RNA-seq analysis', 'DESeq2', 'differential gene expression') but misses common synonyms like 'differential expression' alone and any file extensions, so it falls just below the comprehensive anchor.	4 / 5
Distinctiveness Conflict Risk	The DESeq2/PyDESeq2 niche is distinct with a specific trigger term, but without an explicit 'Use when' clause there is minor overlap risk with other RNA-seq or bioinformatics skills.	4 / 5
	Total	16 / 20 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
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	13 / 16 Passed

Repository: synthetic-sciences/openscience
Path: backend/cli/skills/biology/pydeseq2/SKILL.md
Commit: 5f2a37b

Reviewed: 1 day ago

Table of Contents

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