graphical-abstract-wizard

Generate graphical abstract layout recommendations based on paper abstracts.

Quality

55%

Does it follow best practices?

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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/graphical-abstract-wizard/SKILL.md

Quality

Content

57%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 executable commands, a parameter table, and concrete example output, but it is padded with generic boilerplate sections and lacks a domain-specific workflow with concrete validation checkpoints.

Suggestions

Remove or condense generic boilerplate (When to Use restatements, Key Features, Implementation Details, Output Requirements, Response Template) that adds no domain-specific value.

Dedupe the repeated py_compile/--help command blocks (Quick Check, Audit-Ready Commands, Usage) into a single validation section.

Replace the generic Workflow steps with a domain-specific sequence for producing a graphical abstract, including a concrete validation checkpoint on the generated output.

Dimension	Reasoning	Score
Conciseness	Several sections are generic boilerplate that restates the description or adds process advice applicable to any skill (When to Use, Key Features, Implementation Details, Output Requirements, Response Template), and command instructions are repeated across Quick Check, Audit-Ready Commands, and Usage.	2 / 5
Actionability	Provides copy-paste-ready CLI commands, a full parameter table, three runnable examples, and a concrete example output including a layout diagram and actual Midjourney/DALL-E prompts covering the common cases.	5 / 5
Workflow Clarity	A sequenced Workflow and Error Handling section exist, but the steps are generic process guidance rather than a domain-specific sequence, and there are no concrete validation checkpoints on the actual deliverable for batch/file operations.	3 / 5
Progressive Disclosure	The script reference (scripts/main.py) is clean and one level deep, but the body is a long monolithic document with inlined content (security checklist, risk table, full example output) that could be split into separate reference files.	3 / 5
	Total	13 / 20 Passed

Description

53%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 states a clear single-purpose 'what' for a distinct niche but provides no explicit 'when to use' trigger guidance and only one concrete action, with limited keyword variation.

Suggestions

Add an explicit 'Use when...' clause naming concrete triggers (e.g., 'Use when creating graphical abstracts, visual abstracts, or figure summaries for research papers').

List the skill's multiple concrete capabilities (element suggestions, visual arrangements, Midjourney/DALL-E prompts) rather than a single 'generate layout recommendations' action.

Include natural synonyms and file-relevant terms users say (visual abstract, figures, journal cover) to improve trigger-term coverage.

Dimension	Reasoning	Score
Specificity	Names the domain and one concrete action ('Generate graphical abstract layout recommendations') but omits the multiple capabilities the body mentions (element suggestions, AI art prompts, visual arrangements), so coverage is not comprehensive.	3 / 5
Completeness	The 'what' is clearly stated, but there is no 'Use when...' clause or equivalent explicit trigger guidance, which caps completeness at 3 per the rubric.	3 / 5
Trigger Term Quality	'graphical abstract' and 'paper abstracts' are relevant domain keywords, but common variations users would say (visual abstract, figures, research summary, poster) and file extensions are missing.	3 / 5
Distinctiveness Conflict Risk	'Graphical abstract' is a clear niche unlikely to trigger for unrelated skills, with only minor overlap risk against general research/paper skills.	4 / 5
	Total	13 / 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/graphical-abstract-wizard/SKILL.md
Commit: f5ef65b

Reviewed: ~3 hours ago

Table of Contents

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