gget

Fast CLI/Python queries to 20+ bioinformatics databases. Use for quick lookups: gene info, BLAST searches, AlphaFold structures, enrichment analysis. Best for interactive exploration, simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices.

Quality

76%

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High

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

Quality

Content

65%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 with concrete executable examples throughout, but it underuses progressive disclosure by inlining parameter reference detail that duplicates a dedicated reference file and by leaving the bundled scripts unlinked, and its workflows lack the validation checkpoints the rubric requires for batch operations.

Suggestions

Move the per-module parameter/flag tables and detailed examples into references/module_reference.md and keep SKILL.md as a concise overview with one-line module summaries plus links, to improve conciseness and progressive_disclosure.

Add explicit validation checkpoints to the Common Workflows (e.g., verify returned IDs are non-empty before passing to gget.info, confirm COSMIC TSV download completed before querying) to raise workflow_clarity above the batch-operation cap.

Reference the bundled scripts/ files (batch_sequence_analysis.py, enrichment_pipeline.py, gene_analysis.py) in the relevant workflows or a scripts section so they are discoverable rather than orphaned.

Dimension	Reasoning	Score
Conciseness	The body is accurate and avoids novice-concept padding, but it inlines ~700 lines of per-module parameter reference that substantially duplicates references/module_reference.md, so it is mostly efficient but carries a lot of content that has a dedicated home.	3 / 5
Actionability	Every module ships concrete CLI commands, Python calls, real example sequences/IDs, and specific flags; examples are overwhelmingly copy-paste ready across the common cases (only minor placeholder use like "MKWMFK...").	5 / 5
Workflow Clarity	Six numbered Common Workflows give clear sequences, but batch/large operations (up to ~1000 Ensembl IDs, COSMIC downloads, AlphaFold/cBioPortal runs) have no validation checkpoints or error-recovery feedback loops, triggering the cap for batch operations without validation.	3 / 5
Progressive Disclosure	A Resources section signals the three reference files, but the bulk of the body is reference-grade module detail that should live in module_reference.md, and the three scripts/ Python files are never referenced or linked anywhere in the body.	3 / 5
	Total	14 / 20 Passed

Description

87%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 strong: it concisely states capabilities, gives concrete natural trigger terms, and explicitly covers both what and when with helpful boundary guidance to sibling skills. It sits just below top on specificity and trigger-term completeness because the action list is representative rather than exhaustive.

Dimension	Reasoning	Score
Specificity	Lists several concrete actions ("gene info, BLAST searches, AlphaFold structures, enrichment analysis") across "20+ bioinformatics databases," matching the "several specific actions; minor gaps" anchor rather than the exhaustive 5-level list.	4 / 5
Completeness	Explicitly states what it does ("Fast CLI/Python queries to 20+ bioinformatics databases" plus named actions) and when to use it ("Use for quick lookups," "Best for interactive exploration, simple queries"), with concrete trigger phrases and boundary routing.	5 / 5
Trigger Term Quality	Natural user-facing terms like "gene info," "BLAST searches," "AlphaFold structures," "enrichment analysis," and "quick lookups" give good coverage; a few common synonyms (e.g., "protein structure" beyond AlphaFold) are absent, keeping it just below 5.	4 / 5
Distinctiveness Conflict Risk	A clear bioinformatics-DB niche with explicit routing to alternatives ("use biopython" for batch, "use bioservices" for multi-database workflows) minimizes conflict risk, matching the "clear niche with distinct triggers" anchor.	5 / 5
	Total	18 / 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 (871 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/gget/SKILL.md
Commit: 3a6c3a9

Reviewed: 1 day ago

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