deeptools

NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualization.

Quality

71%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

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

Quality

Content

85%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 content is highly actionable and well-structured, with clear sequenced workflows, validation checkpoints, and exemplary one-level-deep progressive disclosure to real reference files. Its only weakness is mild verbosity from inline content and example walkthroughs that could be delegated to references.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient and well-structured, but at ~520 lines it inlines content that could be delegated (genome-size table, full parameter listings, repeated command examples, three example-interaction walkthroughs), so it sits between efficient and slightly verbose rather than fully lean.	3 / 5
Actionability	Provides copy-paste-ready, executable commands throughout (bamCoverage, bamCompare, computeMatrix, plotHeatmap, validate_files.py, workflow_generator.py) covering the common cases with concrete parameters and flags.	5 / 5
Workflow Clarity	Workflows are clearly sequenced (QC -> Normalization -> Comparison/Visualization) with an explicit 'validate files first' checkpoint, numbered steps, and result-interpretation guidance for error recovery.	5 / 5
Progressive Disclosure	SKILL.md serves as a clear overview with well-signaled, one-level-deep references (tools_reference.md, workflows.md, normalization_methods.md, effective_genome_sizes.md) plus scripts and assets, all real files with explicit 'Use this reference when' navigation cues.	5 / 5
	Total	18 / 20 Passed

Description

58%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 concrete and distinct within the NGS niche, but it omits an explicit 'Use when...' trigger clause, which the rubric caps at completeness 3 and weakens trigger-term quality. Adding natural user phrasing and a clear when-to-use clause would lift it from mid-range toward the top anchors.

Suggestions

Append an explicit 'Use when...' clause listing natural trigger phrases (e.g., 'Use when analyzing ChIP-seq, RNA-seq, or ATAC-seq data, converting BAM to bigWig, or generating heatmaps and QC plots').

Add user-natural synonyms and file extensions (e.g., '.bam', '.bw', 'coverage track', 'ChIP quality') to improve trigger-term coverage.

Expand the action list slightly (e.g., 'compute matrices around features', 'enrichment at peaks') to reach comprehensive specificity at score 5.

Dimension	Reasoning	Score
Specificity	Lists several concrete actions ('BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks)') with only minor coverage gaps, fitting the 'several specific actions' anchor rather than the fully comprehensive score 5.	4 / 5
Completeness	Has a clear 'what' via enumerated capabilities but no explicit 'when/Use when' trigger guidance; per the rubric a missing 'Use when...' clause caps completeness at 3.	3 / 5
Trigger Term Quality	Includes relevant domain keywords ('ChIP-seq, RNA-seq, ATAC-seq', QC, correlation, PCA) but lacks a 'Use when...' clause and common natural phrasings a user would actually say, leaving it with some relevant keywords but missing variations.	3 / 5
Distinctiveness Conflict Risk	Targets a distinct NGS/deepTools niche with specific experiment-type triggers, so mostly distinct with only minor overlap risk against closely related bioinformatics skills.	4 / 5
	Total	14 / 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 (531 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/deeptools/SKILL.md
Commit: 3a6c3a9

Reviewed: 1 day ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.