gget

Fast CLI/Python queries to 20+ bioinformatics databases. Use for quick lookups: gene info, BLAST/BLAT, viral sequence downloads, AlphaFold structures, enrichment analysis, OpenTargets, COSMIC, CELLxGENE, and 8cube mouse specificity/expression data. Best for interactive exploration and simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices.

Quality

82%

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Securityby

Passed

No findings from the security scan

Quality

Content

72%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.

Well-structured overview that practices good progressive disclosure by routing detailed module and workflow content to verified reference files. The main weakness is workflow clarity: batch and resumable operations are mentioned without explicit validate-then-proceed checkpoints in the body itself.

Suggestions

Add an explicit validation/recovery checkpoint for batch operations, e.g. a numbered virus-download workflow with 'verify completeness, then re-run with --merge-results if incomplete'.

Replace the generic 'gget <module> [arguments]' Quick Start template with at least one fully worked, copy-paste example (e.g. a real gget info or gget blast invocation with expected output).

Consolidate the repeated version-pinning guidance into a single 'Reproducibility' callout to trim duplication.

Dimension	Reasoning	Score
Conciseness	Lean overview that defers bulk API detail to references rather than inlining it, with only minor repetition (version-pinning guidance appears in multiple sections) and some time-sensitive version detail that could be further consolidated.	4 / 5
Actionability	Provides concrete executable commands (uv pip install, flag mappings, output-format rules) and a usage pattern, though the Quick Start relies on a generic template rather than a fully worked copy-paste module example.	4 / 5
Workflow Clarity	Sections are well organized and point to worked pipelines, but the body itself lacks explicit validation checkpoints for batch operations (virus downloads, batch gget info); per the rubric, missing validation in batch workflows caps this dimension at 3.	3 / 5
Progressive Disclosure	Clear overview with well-signaled, one-level-deep markdown links to real reference files (module_catalog, module_reference, common_workflows, workflows, database_info), with content appropriately split and easy to navigate.	5 / 5
	Total	16 / 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, third-person description that concretely enumerates capabilities and databases, gives explicit use-trigger guidance, and adds disambiguating boundary advice. Its only gap is slightly less exhaustive synonym/extension coverage among trigger terms.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions and named databases (gene info, BLAST/BLAT, viral sequence downloads, AlphaFold structures, enrichment analysis, OpenTargets, COSMIC, CELLxGENE, 8cube), giving comprehensive coverage of the tool's capabilities.	5 / 5
Completeness	Explicitly answers both what ('Fast CLI/Python queries to 20+ bioinformatics databases' with a concrete list) and when ('Use for quick lookups', 'Best for interactive exploration and simple queries') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Strong natural keyword coverage (BLAST, AlphaFold, enrichment analysis, gene info, viral sequences) that bioinformatics users would actually say, though it lacks broader synonyms or file extensions to fully reach comprehensive.	4 / 5
Distinctiveness Conflict Risk	Clear niche (gget bioinformatics queries) with explicit boundary guidance steering batch/advanced cases to biopython and multi-database workflows to bioservices, minimizing conflict risk.	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: K-Dense-AI/scientific-agent-skills
Path: skills/gget/SKILL.md
Commit: 49c6e97

Reviewed: 9 days ago

Table of Contents

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