geo-database

Access NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.

Quality

66%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./scientific-skills/geo-database/SKILL.md

Quality

Discovery

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.

This is a strong, domain-specific description with excellent technical terminology that bioinformaticians would naturally use. The main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. The specificity and distinctiveness are excellent for a specialized genomics tool.

Suggestions

Add an explicit 'Use when...' clause, e.g., 'Use when the user asks about gene expression data, GEO datasets, or needs to download genomics data from NCBI.'

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: 'Search/download microarray and RNA-seq datasets', 'retrieve SOFT/Matrix files', with specific identifiers (GSE, GSM, GPL) and clear domain (transcriptomics and expression analysis).	3 / 3
Completeness	Clearly answers 'what' (access GEO, search/download datasets, retrieve files) but lacks an explicit 'Use when...' clause. The triggers are implied through domain terms but not explicitly stated.	2 / 3
Trigger Term Quality	Excellent coverage of natural terms users would say: 'NCBI GEO', 'gene expression', 'genomics', 'microarray', 'RNA-seq', 'GSE', 'GSM', 'GPL', 'SOFT', 'Matrix files', 'transcriptomics'. These are terms bioinformaticians would naturally use.	3 / 3
Distinctiveness Conflict Risk	Highly distinctive with specific database (NCBI GEO), file types (SOFT/Matrix), and identifiers (GSE, GSM, GPL). Very unlikely to conflict with other skills due to the specialized bioinformatics domain.	3 / 3
	Total	11 / 12 Passed

Implementation

50%

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

This skill provides comprehensive, actionable guidance for accessing GEO data with excellent executable code examples, but suffers from severe verbosity that wastes context window space. The content explains basic concepts Claude already knows and includes extensive inline material that should be in reference files. Workflow clarity is adequate but lacks explicit validation steps for data integrity.

Suggestions

Reduce content by 60-70% by removing explanatory text about what GEO is, how data is organized, and basic concepts - keep only the actionable code patterns and critical gotchas

Move detailed analysis examples (QC, differential expression, clustering) to a separate ANALYSIS.md reference file, keeping only a brief pointer in the main skill

Add explicit validation steps after downloads (e.g., 'Verify file exists and is non-empty before parsing') and error handling patterns for common failures

Consolidate repetitive code patterns - the multiple search functions and batch processing examples could be reduced to one canonical pattern with variations noted briefly

Dimension	Reasoning	Score
Conciseness	The skill is extremely verbose at 600+ lines, explaining concepts Claude already knows (what GEO is, what PDFs are equivalent explanations for genomics), includes extensive background on data organization that could be summarized in a few lines, and repeats similar code patterns multiple times.	1 / 3
Actionability	The skill provides fully executable Python code examples throughout, with complete import statements, function definitions, and copy-paste ready snippets for searching, downloading, and analyzing GEO data.	3 / 3
Workflow Clarity	While steps are listed for various operations, there are no explicit validation checkpoints or error recovery feedback loops. The batch processing sections lack verification steps to confirm successful downloads before proceeding with analysis.	2 / 3
Progressive Disclosure	The skill mentions a reference file (references/geo_reference.md) but includes massive amounts of content inline that should be split out. The 600+ line monolithic structure with 7 major sections could benefit from better organization across multiple files.	2 / 3
	Total	8 / 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 — 9 / 11 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (815 lines); consider splitting into references/ and linking	Warning
metadata_version	'metadata.version' is missing	Warning

	Total	9 / 11 Passed

Repository: googolme/run0204
Commit: 4902409

Reviewed: about 1 month ago

Table of Contents

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