glycobiology

Glycosylation site prediction and glycobiology analysis. N-glycosylation motif finding, O-glycosylation hotspot prediction, glycan structure resources. Lightweight, pure Python. For protein function queries use uniprot-database; for structure analysis use alphafold-database.

Quality

73%

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Securityby

Passed

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

Quality

Content

71%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 code-rich, highly actionable skill body with clear sections, worked examples, and a useful validation-oriented workflow. Its weaknesses are redundant duplicate function definitions and an orphaned bundle script that is never referenced from the main file.

Suggestions

Reference the bundled script (e.g., 'Full implementation: see scripts/predict_glycosylation.py') and avoid duplicating the N-glycosylation finder in both Quick Start and Core Capabilities.

Add an explicit verification step to Workflow 1 (e.g., cross-check predicted N-sites against UniProt annotations) to strengthen the validation checkpoint.

Move the GLYCAN_TOOLS dictionary into a reference file and link to it from the body to reduce inline bulk and improve navigation.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient code, but the N-glycosylation finder is defined twice — a simplified version in Quick Start and an expanded version in Core Capability #1 — which is redundant padding that could be tightened.	3 / 5
Actionability	Provides fully executable, copy-paste-ready functions with concrete worked examples (human EPO, sample sequences) covering the common N- and O-glycosylation cases.	5 / 5
Workflow Clarity	Two clear Typical Workflows are sequenced, and Workflow 2 (compare predicted vs UniProt-annotated sites) functions as a built-in validation checkpoint; minor gaps remain in explicit verify-step language.	4 / 5
Progressive Disclosure	Section organization is good, but the full code implementations are inlined in SKILL.md while the bundled scripts/predict_glycosylation.py is never referenced or signaled, so content that belongs in a separate file is not split out.	3 / 5
	Total	15 / 20 Passed

Description

75%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, concrete, third-person description that names specific capabilities and actively disambiguates from neighboring skills. Its main weakness is the absence of an explicit 'Use when...' trigger phrase, leaving the invocation condition only implied.

Suggestions

Add an explicit trigger clause such as 'Use when predicting or annotating glycosylation sites on protein sequences, or surveying glycan-analysis tools.'

Include a couple of natural synonyms users might say (e.g., 'sugar modifications', 'carbohydrate attachment') to broaden trigger coverage.

Dimension	Reasoning	Score
Specificity	Names multiple specific concrete actions — 'N-glycosylation motif finding, O-glycosylation hotspot prediction, glycan structure resources' — giving comprehensive coverage of the glycobiology niche, matching the anchor for listing multiple specific actions.	5 / 5
Completeness	The 'what' is clear and concrete, but there is no explicit 'Use when...' trigger clause; the only conditional guidance routes away to other skills, so 'when' is only weakly implied — capped at 3 per the missing-trigger guideline.	3 / 5
Trigger Term Quality	Includes natural domain terms a user would say ('glycosylation site prediction', 'glycan structure resources'), but lacks broader synonyms or file-extension-style variations, so a few natural terms are missing.	4 / 5
Distinctiveness Conflict Risk	Occupies a clear niche (glycobiology) and explicitly reduces conflict risk by routing related needs elsewhere ('For protein function queries use uniprot-database; for structure analysis use alphafold-database').	5 / 5
	Total	17 / 20 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
metadata_version	'metadata.version' is missing	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: synthetic-sciences/openscience
Path: backend/cli/skills/biology/glycobiology/SKILL.md
Commit: 3a6c3a9

Reviewed: 1 day ago

Table of Contents

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