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Get Started Free →Guides educational visual asset creation using professional creative briefs, proficiency alignment, prerequisite validation, and duplicate prevention.
.claude/skills/aiskillstore-visual-asset-workflow/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-01 | ✗→✓ | ▲ Improved | 851% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 13% | 0% |
| case-05 | ✗→✓ | ▲ Improved | -14% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 207% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 86% | 0% |
Educational visual generation converges toward generic infographics with technical specifications ("44pt Roboto Bold, 250px box") that activate prediction mode instead of reasoning mode. This produces bland, PowerPoint-default aesthetics instead of distinctive, pedagogically effective visuals.
This skill provides professional creative brief methodology to activate Gemini 3's reasoning capabilities.
Avoid: Jumping into visual analysis without context Prefer: Strategic planning phase (Q0)
Read FIRST:
apps/learn-app/docs/chapter-index.md → Extract part, proficiency (A2/B1/C2), prerequisitesapps/learn-app/docs/[part]/[chapter]/README.md → Understand lesson structureDetect conflicts BEFORE work:
Output strategic plan, WAIT for approval before proceeding.
Principle: Plan prevents wasted work (Chapter 9 failure: 5 wrong lessons from skipping planning)
Avoid: Technical specifications
❌ "Title: 44pt Roboto Bold at (50, 20)"
❌ "Box: 250px × 90px, #aaaaaa, 8px corners"
❌ "Shadow: 4px offset, 8px blur"Prefer: Story + Intent + Metaphor
✅ The Story: [1-2 sentence narrative of what's visualized]
✅ Emotional Intent: Should feel [exponential growth, surprising magnitude]
✅ Visual Metaphor: [Multiplication cascade - like compound interest]
✅ Key Insight: [ONE thing students must grasp]
✅ Color Semantics: Blue (#2563eb) = Authority (teaches governance concept)
✅ Typography Hierarchy: Largest = Key insight (not arbitrary sizing)
✅ Pedagogical Reasoning: Why these choices serve teachingPrinciple: Creative briefs activate reasoning mode; specifications activate prediction mode
Why it matters: Gemini 3 reasons about HOW to achieve intent → Distinctive visuals instead of generic
When: Batch mode with >8 visuals OR continuation session
Apply condensation while preserving reasoning activation:
ALWAYS KEEP:
CONDENSE:
NEVER REMOVE:
Example:
FULL: "Top Layer shows the Coordinator at center top with label..."
CONDENSED: "Top Layer - Coordinator: Center top: 'Orchestrator'..."Target: 60-70% token reduction, 100% reasoning activation preserved
Principle: Efficiency through compression, not through elimination of reasoning triggers
Avoid: One-size-fits-all complexity
Prefer: Proficiency-gated constraints
A2 Beginner (Non-negotiable limits):
B1 Intermediate:
C2 Professional:
Principle: Overwhelming A2 students = learning failure; artificial simplicity for C2 = patronizing
Avoid: Assuming knowledge students don't have
Prefer: Validate against chapter prerequisites
Detection:
Example Violations:
Exception: Meta-level teaching OK
Principle: Visual cannot require unknown knowledge
Avoid: Decorative visuals without pedagogical purpose
Prefer: Every visual serves specific learning objective
Principle 3 (Factual Accuracy):
Principle 7 (Minimal Content):
Principle: Visual decisions align with project constitution
Avoid: Layer mismatch
Prefer: Visual approach matches chapter's pedagogical layer
L1 (Manual Foundation):
L2 (AI Collaboration):
L3 (Intelligence Design):
L4 (Spec-Driven):
Principle: Visual design reinforces pedagogical approach
Avoid: Generating different prompts that produce the same visual
Prevent BEFORE generation:
*.png files in target chapter directory*.prompt.md filesDetect AFTER generation (in image-generator):
Principle: Prevention cheaper than rework
Never:
Even if it seems reasonable:
You tend to default to comparison diagrams even with story-driven prompts. Vary visual types:
Match visual type to story, not habit.
After batch completion, analyze systematically (Q8):
Success patterns:
Failure analysis:
Continuous improvement:
Document in: history/visual-assets/reflections/chapter-{NN}-reflection.md
Principle: Systematic reflection → Improved future performance
You'll know this skill is working when:
Result: Professional-quality visuals that teach effectively, generated efficiently through planning, with zero duplicates requiring rework.
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-02 | fail→fail | 33,545 | 27,212 | -19% | 1 | 1 | 0% | 5,169 | 6,761 | +31% | 0 | 0 | — |
case-01 | fail→pass | 3,697 | 12,998 | +252% | 1 | 1 | 0% | 456 | 4,335 | +851% | 0 | 0 | — |
case-03 | fail→fail | 20,840 | 13,744 | -34% | 1 | 1 | 0% | 3,167 | 4,370 | +38% | 0 | 0 | — |
case-04 | fail→pass | 20,318 | 9,987 | -51% | 1 | 1 | 0% | 3,370 | 3,807 | +13% | 0 | 0 | — |
case-05 | fail→pass | 23,205 | 8,594 | -63% | 1 | 1 | 0% | 4,128 | 3,551 | -14% | 0 | 0 | — |
case-06 | fail→pass | 7,370 | 10,508 | +43% | 1 | 1 | 0% | 1,281 | 3,936 | +207% | 0 | 0 | — |
case-07 | fail→pass | 11,888 | 5,766 | -51% | 1 | 1 | 0% | 1,702 | 3,160 | +86% | 0 | 0 | — |
case-08 | pass→pass | 13,246 | 9,371 | -29% | 1 | 1 | 0% | 2,081 | 3,695 | +78% | 0 | 0 | — |
case-09 | pass→pass | 12,695 | 8,695 | -32% | 1 | 1 | 0% | 2,030 | 3,678 | +81% | 0 | 0 | — |
case-10 | fail→pass | 14,429 | 9,657 | -33% | 1 | 1 | 0% | 2,421 | 3,799 | +57% | 0 | 0 | — |
case-11 | fail→pass | 13,144 | 10,865 | -17% | 1 | 1 | 0% | 1,995 | 3,929 | +97% | 0 | 0 | — |
case-12 | fail→pass | 8,765 | 4,066 | -54% | 1 | 1 | 0% | 1,303 | 2,867 | +120% | 0 | 0 | — |
case-13 | pass→fail | 15,893 | 11,249 | -29% | 1 | 1 | 0% | 2,387 | 3,905 | +64% | 0 | 0 | — |
case-14 | pass→pass | 18,653 | 11,096 | -41% | 1 | 1 | 0% | 2,665 | 3,799 | +43% | 0 | 0 | — |
case-15 | fail→pass | 14,568 | 2,122 | -85% | 1 | 1 | 0% | 2,062 | 2,604 | +26% | 0 | 0 | — |
case-16 | pass→pass | 8,423 | 5,081 | -40% | 1 | 1 | 0% | 1,266 | 2,989 | +136% | 0 | 0 | — |
case-17 | fail→pass | 10,301 | 2,883 | -72% | 1 | 1 | 0% | 1,521 | 2,689 | +77% | 0 | 0 | — |
case-18 | pass→pass | 13,438 | 6,432 | -52% | 1 | 1 | 0% | 2,138 | 3,277 | +53% | 0 | 0 | — |
case-19 | pass→pass | 31,112 | 14,469 | -53% | 1 | 1 | 0% | 6,163 | 5,273 | -14% | 0 | 0 | — |
case-20 | pass→pass | 25,541 | 20,811 | -19% | 1 | 1 | 0% | 4,211 | 5,575 | +32% | 0 | 0 | — |
case-21 | pass→pass | 11,418 | 8,730 | -24% | 1 | 1 | 0% | 2,378 | 4,058 | +71% | 0 | 0 | — |
case-22 | pass→pass | 11,129 | 9,173 | -18% | 1 | 1 | 0% | 2,264 | 4,050 | +79% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +41 percentage points is the difference between those two pass rates over the 22 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.