western-blot-quantifier

Automatically identify Western Blot gel bands, perform densitometric analysis, and calculate normalized values relative to loading controls.

Quality

59%

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Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./scientific-skills/Data Analysis/western-blot-quantifier/SKILL.md

Quality

Content

48%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 actionable and workflow-oriented but padded with generic boilerplate and a class-name mismatch that breaks the examples. Trimming meta-sections and aligning the documented API with the actual scripts would materially improve it.

Suggestions

Reconcile the documented class/import path with scripts/main.py: the doc references 'WesternBlotQuantifier' but main.py defines 'WBQuantifier' (and __init__.py imports a name main.py does not export), so the example code will fail.

Remove or compress generic boilerplate (Lifecycle Status, Risk Assessment, Security Checklist, Evaluation Criteria, Output Requirements, Response Template) that restates knowledge Claude already has, and stop repeating the description verbatim across sections.

Move the long Algorithm Description, Examples, and parameter tables into one-level-deep reference files (e.g., ALGORITHM.md, EXAMPLES.md) referenced from SKILL.md to improve progressive disclosure.

Dimension	Reasoning	Score
Conciseness	Noticeably verbose: the description is repeated verbatim across 'When to Use' and 'Key Features', and many generic boilerplate sections (Output Requirements, Response Template, Lifecycle Status, Risk Assessment, Security Checklist, Evaluation Criteria) restate process concepts Claude already knows.	2 / 5
Actionability	Provides concrete code and CLI examples plus an output CSV schema, but the documented import path and 'WesternBlotQuantifier' class do not match the actual scripts/main.py (which defines 'WBQuantifier'), so the examples are not executable as written.	3 / 5
Workflow Clarity	A clear sequenced Workflow with validation checkpoints and an Error Handling fallback path is present; minor gaps keep it just below the explicit validate-fix-retry feedback loop of a 5.	4 / 5
Progressive Disclosure	Structure exists via section headers and a real scripts/ bundle, but the SKILL.md is a monolithic single file with large inlined blocks (algorithm description, examples, security/risk tables) that would read better split into one-level-deep reference files.	3 / 5
	Total	12 / 20 Passed

Description

70%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 specific and targets a well-defined niche, but it omits any explicit trigger/usage guidance, capping its completeness. Adding a 'Use when...' clause with natural trigger phrases would raise the score.

Suggestions

Add an explicit 'Use when...' clause naming natural trigger phrases (e.g., 'Use when quantifying Western Blot bands, performing densitometry, or normalizing target proteins to loading controls like GAPDH or β-actin').

Include common synonyms and gel-image file extensions (immunoblot, WB, .tif/.png gel scans) to broaden trigger term coverage.

Consider naming one more concrete action (e.g., background correction or CSV export) to push specificity toward a 5.

Dimension	Reasoning	Score
Specificity	Lists several concrete actions ('identify Western Blot gel bands', 'perform densitometric analysis', 'calculate normalized values relative to loading controls') with only minor coverage gaps, but stops short of the comprehensive multi-action list needed for a 5.	4 / 5
Completeness	Clearly states what the skill does but lacks any explicit 'Use when...' trigger clause; per the rubric a missing trigger guidance caps completeness at 3.	3 / 5
Trigger Term Quality	Good coverage of natural domain terms a researcher would say ('Western Blot', 'gel bands', 'densitometric analysis', 'loading controls'), but misses common synonyms/extensions like 'immunoblot', 'WB', or gel image file formats.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche (Western Blot densitometry/normalization) with distinct triggers and minimal overlap risk with other skills.	5 / 5
	Total	16 / 20 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: aipoch/medical-research-skills
Path: scientific-skills/Data Analysis/western-blot-quantifier/SKILL.md
Commit: f5ef65b

Reviewed: ~10 hours ago

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