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.

Quality

68%

Does it follow best practices?

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Securityby

Low

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

Quality

Content

78%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 copy-paste CLI examples and well-structured progressive disclosure to verified reference files, but contains some redundancy across the Quick Start and Research Integration sections.

Suggestions

Consolidate the redundant CLI examples in Research Integration with Quick Start, keeping only the --research-specific variations.

Trim marketing phrasing ('Simply describe what you want', 'Professional-ready output in minutes') that does not add instructional value.

Inline a brief 4-step summary of the iterative-refinement feedback loop so the workflow is self-contained before pointing to the reference.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with offloaded detail, but the 'How it works' bullets, 'What happens behind the scenes', and the Research Integration CLI examples repeat patterns already shown in Quick Start, and marketing phrases like 'Simply describe what you want' add padding.	3 / 5
Actionability	Provides fully executable, copy-paste-ready CLI commands covering common cases (type, doc-type, style, palette, --research) with concrete flags and output paths.	5 / 5
Workflow Clarity	The generate-review-refine loop is sequenced with an explicit validation checkpoint (quality score vs threshold) and a feedback loop (improve prompt → regenerate), plus a Quick Reference Checklist; the detailed loop resides in a reference file rather than inline, a minor gap.	4 / 5
Progressive Disclosure	Clear overview with well-signaled one-level-deep references (infographic_type_catalog.md, infographic_types.md, iterative_refinement.md, design_principles.md, color_palettes.md — all verified present) and content appropriately split between body and references.	5 / 5
	Total	17 / 20 Passed

Description

58%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 clearly states what the skill does and names specific capabilities, but omits any explicit 'when to use' trigger guidance and lacks natural keyword synonyms beyond 'infographics'.

Suggestions

Add an explicit 'Use when...' clause naming natural trigger phrases (e.g., 'Use when creating infographics, visualizing data as charts, or summarizing points visually').

Include common synonyms users would say — 'charts', 'data visualization', 'visual summaries' — not just 'infographics'.

Briefly distinguish the niche from adjacent skills (e.g., 'For non-infographic images use generate-image; for technical schematics use scientific-schematics').

Dimension	Reasoning	Score
Specificity	Lists several concrete actions ('Create professional infographics', 'smart iterative refinement', 'quality review', 'research-lookup and web search') plus specific capabilities (10 types, 8 styles, colorblind palettes), with only minor coverage gaps.	4 / 5
Completeness	The 'what' is clearly stated ('Create professional infographics...') 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	Contains the natural term 'infographics' but lacks common synonyms users would say ('charts', 'data visualization', 'visualize data'); 'research-lookup' and 'web search' are tool references rather than user phrasings.	3 / 5
Distinctiveness Conflict Risk	'infographics using Nano Banana Pro AI' is a clear niche with mostly distinct triggers, though it has minor overlap risk with closely related visual skills like generate-image and scientific-schematics.	4 / 5
	Total	14 / 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
metadata_field	'metadata' should map string keys to string values	Warning

	Total	15 / 16 Passed

Repository: K-Dense-AI/scientific-agent-skills
Path: skills/infographics/SKILL.md
Commit: b2a92ba

Reviewed: 3 days ago

Table of Contents

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