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infographics

Create professional infographics using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3.6 Flash for quality review. Integrates research-lookup and web search for accurate data. Supports 10 infographic types, 8 industry styles, and colorblind-safe palettes.

60

Quality

70%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./.claude/skills/infographics/SKILL.md

The canonical home for this skill is infographics in K-Dense-AI/scientific-agent-skills

SKILL.md
Quality
Evals
Security

Quality

Content

75%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 body is highly actionable with excellent executable examples and a clearly sequenced iterative workflow supported by well-organized references. It is slightly let down by redundancy and over-explanation that could be tightened for token efficiency.

Suggestions

Consolidate the 'How it works' and 'What happens behind the scenes' sections to remove redundant explanation of the same pipeline.

Trim the good/bad prompt-engineering tips to only skill-specific guidance, avoiding general 'be specific' advice Claude already knows.

Move the full industry-style and palette tables into their reference files and keep only a brief inline summary plus a link.

DimensionReasoningScore

Conciseness

Mostly efficient with actionable examples, but contains redundancy ('How it works' vs 'What happens behind the scenes') and re-explains basics in the good/bad prompt tips that could be trimmed.

3 / 5

Actionability

Copy-paste-ready bash commands cover the common cases (types, styles, palettes, research) with concrete flags and output paths, fully executable without further inference.

5 / 5

Workflow Clarity

A clear 6-step generate-review-refine sequence with an explicit decision/feedback checkpoint ('If quality >= threshold -> DONE'); the detailed loop is appropriately offloaded to iterative_refinement.md, leaving a minor gap inline.

4 / 5

Progressive Disclosure

Well-signaled one-level-deep references to real files (infographic_type_catalog.md, infographic_types.md, iterative_refinement.md, design_principles.md, color_palettes.md), with minor inlining of style and palette tables that could live in references.

4 / 5

Total

16

/

20

Passed

Description

66%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 capability-rich, clearly communicating what the skill does and its distinguishing features. Its main weakness is the absence of an explicit 'Use when...' trigger clause, leaving the 'when' guidance implicit.

Suggestions

Add an explicit 'Use when...' trigger clause naming natural user phrases (e.g. 'Use when creating infographics, visualizing data or statistics, or presenting timelines and comparisons').

Include common natural synonyms like 'data visualization', 'visualize statistics', or 'chart' to broaden trigger-term coverage.

Briefly distinguish from adjacent skills (e.g. 'For technical/scientific diagrams, use scientific-schematics instead') to reduce overlap risk.

DimensionReasoningScore

Specificity

Names the infographics domain and several concrete capabilities ('smart iterative refinement', 'Gemini 3.6 Flash for quality review', 'research-lookup and web search', '10 infographic types, 8 industry styles, and colorblind-safe palettes'), with only minor gaps in the full action set.

4 / 5

Completeness

Has a clear 'what' but no 'Use when...' clause or equivalent explicit trigger guidance, which caps completeness at 3 per the rubric guideline.

3 / 5

Trigger Term Quality

Good coverage of natural terms ('infographics', 'colorblind-safe palettes', 'industry styles'); missing a few common variations users might say like 'data visualization' or 'visualize data'.

4 / 5

Distinctiveness Conflict Risk

A clear niche (AI-generated infographics with quality review) that is mostly distinct, with only minor overlap risk against closely related visual skills like generate-image or scientific-schematics.

4 / 5

Total

15

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_field

'metadata' should map string keys to string values

Warning

Total

15

/

16

Passed

Repository
K-Dense-AI/claude-scientific-writer
Reviewed

Table of Contents

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