tooluniverse-regulatory-genomics

Transcription factor binding, cis-regulatory elements (cCREs), chromatin accessibility, and regulatory annotation using JASPAR (motifs), ENCODE (cCREs, ChIP-seq), RegulomeDB (regulatory variant scoring), UCSC — plus sequence-based deep-learning prediction of regulatory activity and non-coding variant effects (AlphaGenome, Enformer, Borzoi, ChromBPNet, Evo 2). Use for regulatory element annotation, TF-binding-site prediction, regulatory-region functional impact assessment, and predicting how a non-coding variant or a raw DNA sequence affects expression/chromatin/accessibility. Use this whenever a user asks what regulates a gene, whether a SNP hits a regulatory element, or to predict a non-coding variant's functional effect from sequence.

Quality

78%

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Passed

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tessl review fix ./plugins/tooluniverse/skills/tooluniverse-regulatory-genomics/SKILL.md

Quality

Content

63%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 thorough, well-structured operational skill with strong actionability and a clear phased workflow plus fallbacks. Its main weaknesses are content redundancy across sections and the absence of progressive disclosure — all reference material lives inline in one long file.

Suggestions

Consolidate the Key Tools table and the Tool Parameter Reference table into a single source of truth to remove duplicated tool descriptions and trim token count.

Move the large reference material (Tool Parameter Reference, RegulomeDB rank interpretation table, deep-learning model comparison table) into one-level-deep reference files under references/ and link to them from SKILL.md to improve progressive disclosure.

Tighten or remove the conceptual 'Domain Reasoning' paragraph, keeping only the operational guidance that Claude would not already infer.

Dimension	Reasoning	Score
Conciseness	Mostly efficient operational detail (exact param names, controlled vocabularies) but ~330 lines with real redundancy — tool info appears in both the Key Tools table and the Tool Parameter Reference table, and Common Patterns restates the Workflow phases. The 'Domain Reasoning' paragraph adds conceptual prose that could be trimmed.	3 / 5
Actionability	Provides concrete, copy-paste-ready tool calls with exact parameter values (e.g. `jaspar_search_matrices(name="CTCF", species="Homo sapiens")`, `RegulomeDB_query_variant(rsid="rs4994")`); the Common Patterns section leans toward pseudocode-style flows, which keeps it just below a 5.	4 / 5
Workflow Clarity	Clear phased sequence (Phase 1–4) with a Fallback Strategies table serving as error-recovery guidance and a 'Negative results documented' principle. These are read-only investigative workflows rather than destructive/batch ones, so the validation cap does not apply, though explicit per-phase validation checkpoints are absent.	4 / 5
Progressive Disclosure	Well-organized with clear section headers and tables, but everything is inlined in a single 330-line SKILL.md with no bundle files and no references to separate reference files; the large tool-parameter and RegulomeDB-rank reference tables are candidates for offloading to one-level-deep reference files.	3 / 5
	Total	14 / 20 Passed

Description

92%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 strong, specific description that clearly states both capabilities and explicit 'use when' triggers with natural phrasing. Minor room for improvement in plain-language synonym coverage alongside the technical acronyms.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions — 'Transcription factor binding, cis-regulatory elements (cCREs), chromatin accessibility', 'TF-binding-site prediction, regulatory-region functional impact assessment, and predicting how a non-coding variant or a raw DNA sequence affects expression/chromatin/accessibility' — with comprehensive coverage across annotation and sequence-based prediction.	5 / 5
Completeness	Explicitly answers both 'what' (the data sources and prediction models it uses) and 'when' ('Use for regulatory element annotation...' and 'Use this whenever a user asks what regulates a gene...') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Includes natural user phrasings ('what regulates a gene', 'whether a SNP hits a regulatory element', 'predict a non-coding variant's functional effect from sequence') but is acronym-heavy (JASPAR, ENCODE, cCREs) and lacks the synonym breadth of a 5; it sits above the midpoint because the trigger phrases are genuinely what a user would say.	4 / 5
Distinctiveness Conflict Risk	Occupies a clear niche (regulatory genomics + sequence-based regulatory prediction) with distinct triggers; minimal overlap risk with other skills. Voice is third person throughout, so no voice penalty applies.	5 / 5
	Total	19 / 20 Passed

Validation

100%

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 — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: mims-harvard/ToolUniverse
Path: plugins/tooluniverse/skills/tooluniverse-regulatory-genomics/SKILL.md
Commit: 1b02920

Reviewed: 1 day ago

Table of Contents

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