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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.

61

Quality

72%

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SecuritybySnyk

Low

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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

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.

A well-structured, highly actionable skill body: executable commands throughout, a clearly sequenced generate-review-refine loop with an explicit quality threshold decision point, and exemplary progressive disclosure to verified one-level-deep reference files. The main weakness is padding — a definition of 'infographic', marketing-style benefit bullets, and a redundant closing paragraph — that could be trimmed without losing any instructional value.

Suggestions

Delete the opening definition of 'infographic' (a concept Claude already knows) and the marketing lines ("Professional-ready output in minutes", "No design skills required", "Simply describe what you want...") plus the redundant final closing paragraph.

Trim the ✅ 'Smart Iteration Benefits' list — it sells the feature rather than instructing — and consolidate the Quick Start's six near-identical command examples down to 2-3 that each demonstrate a distinct flag.

Inline the key validation mechanics (how the quality score is checked and what to do on failure) at least briefly in the workflow section instead of deferring all of it to iterative_refinement.md.

DimensionReasoningScore

Conciseness

The bulk of the body is efficient (CLI examples, compact style/palette/threshold tables, troubleshooting), but it includes unnecessary material: it opens by defining what an infographic is ("Infographics are visual representations of information, data, or knowledge..."), a concept Claude already knows, plus marketing padding like "Professional-ready output in minutes", "No design skills required", the ✅ "Smart Iteration Benefits" list, and a redundant closing paragraph. This fits 'mostly efficient but includes some unnecessary explanation or could be tightened'; it is not a 2 because the majority of sections carry real instructional weight.

3 / 5

Actionability

The guidance is fully executable: six copy-paste-ready CLI invocations with all flags shown ("python skills/infographics/scripts/generate_infographic.py '5 benefits of regular exercise' -o figures/exercise_benefits.png --type list"), concrete good/bad prompt examples, per-problem troubleshooting fixes, and a before/after checklist. This matches the 'fully executable; copy-paste ready commands covering common cases' anchor, and nothing is pseudocode.

5 / 5

Workflow Clarity

The generate-review-refine loop is clearly sequenced with an explicit validation checkpoint and decision point ("Review 1: Gemini 3.6 Flash evaluates quality against document-type threshold", "If quality >= threshold → DONE", "If below threshold: Improved prompt based on critique, regenerate"), plus threshold values and error-recovery guidance in Troubleshooting. It falls short of 5 because the loop's operational details (how review scoring and iteration control actually work) are deferred to a reference file, and the checklist items are generic rather than explicit validation commands.

4 / 5

Progressive Disclosure

The body is a genuine overview that pushes bulk detail to real, one-level-deep reference files — type details to infographic_type_catalog.md/infographic_types.md, the refinement loop and full CLI to iterative_refinement.md, with all five referenced files verified present and clearly signaled at point of use. Inline content (style table, palette table, thresholds) is appropriately compact while full specifications live in references, matching the 'clear overview with well-signaled one-level-deep references' anchor; the only nit is listing two overlapping type references, which is too minor to drop the score.

5 / 5

Total

17

/

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.

A specific, capability-rich description with good trigger keywords for the infographic niche, but it omits any explicit 'use when' guidance and lacks common synonyms like 'data visualization' or 'chart'. The enumerated types, styles, and palette support give it strong distinctiveness. Adding a trigger clause would move it from adequate to strong.

Suggestions

Append an explicit trigger clause, e.g. "Use when the user asks for infographics, data visualizations, or visual summaries of statistics, timelines, processes, or comparisons" — the missing 'when' currently caps completeness at 3.

Add natural synonyms and variations users would say — "data visualization", "chart", "visual summary", "poster" — to broaden trigger-term coverage.

State the concrete output (e.g., "generates PNG infographic images") so the 'what' is fully grounded.

DimensionReasoningScore

Specificity

The description lists several concrete capabilities — "Create professional infographics", "smart iterative refinement", "Gemini 3.6 Flash for quality review", "Integrates research-lookup and web search", and enumerated supports ("10 infographic types, 8 industry styles, and colorblind-safe palettes") — which matches the 'several specific actions; minor gaps' anchor. It falls short of a 5 because it never states the concrete deliverable (e.g., generated PNG/image files) or the execution surface, leaving small coverage gaps.

4 / 5

Completeness

The 'what' is clear (create infographics via Nano Banana Pro with iterative quality review and research integration), but there is no 'Use when...' clause or equivalent explicit trigger guidance anywhere in the description, capping completeness at 3 per the judging guidelines. It is not a 4 because 'when' is entirely absent rather than merely imprecise.

3 / 5

Trigger Term Quality

"infographics" is the natural term users would say, reinforced by adjacent user-facing terms like "colorblind-safe palettes", "industry styles", and "quality review" — good coverage per the anchor 4 example. Common synonyms such as "data visualization", "charts", "diagrams", or "poster" are missing, which keeps it below the comprehensive synonym coverage of a 5.

4 / 5

Distinctiveness Conflict Risk

"infographics" is a specific niche with distinct triggers, and the colorblind-palette/types enumeration further differentiates it, matching 'mostly distinct; minor overlap risk'. Minor overlap risk remains with general image-generation or data-visualization skills, and the mention of "research-lookup and web search" could pull triggers meant for research skills.

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.

Validation — 15 / 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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