visual-asset-workflow: Скилл для создания образовательных визуалов

--- name: visual-asset-workflow description: This skill should be used when creating visual assets for educational content. It provides professional creative brief methodology to activate reasoning mode for distinctive, pedagogically effective visuals. version: "1.0.0" --- # Visual Asset Workflow Skill ## Context & Problem 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. --- ## Core Principles 1. **Story activates reasoning** - Narrative intent produces distinctive visuals; technical specs produce generic ones 2. **Proficiency dictates complexity** - A2 students need <5 sec grasp; C2 professionals handle dense information 3. **Prerequisites gate content** - Visuals cannot assume knowledge students don't have yet 4. **Pedagogy drives hierarchy** - Visual weight teaches importance, not arbitrary aesthetics --- ## Dimensional Guidance ### Planning Before Execution **Avoid:** Jumping into visual analysis without context **Prefer:** Strategic planning phase (Q0) Read FIRST: - `robolearn-interface/docs/chapter-index.md` → Extract part, proficiency (A2/B1/C2), prerequisites - `robolearn-interface/docs/[part]/[chapter]/README.md` → Understand lesson structure Detect conflicts BEFORE work: - Proficiency-complexity mismatch (complex visual for A2 beginners) - Prerequisite violations (Python code when students haven't learned it) - Pedagogical layer incoherence (Layer 1 content using Layer 4 approaches) Output strategic plan, WAIT for approval before proceeding. **Principle:** Plan prevents wasted work (Chapter 9 failure: 5 wrong lessons from skipping planning) --- ### Prompt Structure: Professional Creative Briefs **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 teaching ``` **Principle:** 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 --- ### Token Conservation Strategy **When:** Batch mode with >8 visuals OR continuation session **Apply condensation while preserving reasoning activation:** **ALWAYS KEEP:** - Story (1-2 sentence narrative) - Emotional Intent (what it should FEEL like) - Visual Metaphor (universal concept) - Key Insight (ONE thing students must grasp) - Color semantics with hex codes (#2563eb) - Pedagogical reasoning (why these choices) **CONDENSE:** - Long examples → Short labels - Verbose descriptions → Bullet points - Repeated patterns → Compact notation **NEVER REMOVE:** - Narrative elements - Intent statements - Reasoning explanations **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 --- ### Proficiency-Complexity Alignment **Avoid:** One-size-fits-all complexity **Prefer:** Proficiency-gated constraints **A2 Beginner** (Non-negotiable limits): - Max 5-7 elements - <5 second grasp - Static only (no interactive) - Max 2×2 grids - Clear hierarchy (largest = most important) **B1 Intermediate**: - Max 7-10 elements - <10 second grasp - Interactive Tier 1 OK (tap-to-reveal) - Max 3×3 grids **C2 Professional**: - No artificial limits - Dense infographics OK - Full interactive architecture - Production complexity **Principle:** Overwhelming A2 students = learning failure; artificial simplicity for C2 = patronizing --- ### Prerequisite Validation Gate **Avoid:** Assuming knowledge students don't have **Prefer:** Validate against chapter prerequisites **Detection:** - Check Part number: Part 1-2 = no programming, Part 3 = markdown/prompts, Part 4+ = Python - Check prerequisite list from chapter-index.md **Example Violations:** - ❌ Python code in Chapter 9 (Part 3 - students haven't learned it) - ❌ Git commands in Part 2 (students haven't learned CLI) **Exception:** Meta-level teaching OK - ✅ Teaching "markdown code block syntax" by showing Python code block (teaches markdown, not Python) **Principle:** Visual cannot require unknown knowledge --- ### Constitutional Alignment **Avoid:** Decorative visuals without pedagogical purpose **Prefer:** Every visual serves specific learning objective **Principle 3 (Factual Accuracy):** - Verify all statistics, dates, technical specs - Enable Google Search grounding for factual claims - Cite sources for data **Principle 7 (Minimal Content):** - Reject "let's add a visual for variety" - Every element must teach something - Remove non-teaching decoration **Principle:** Visual decisions align with project constitution --- ### Pedagogical Layer Coherence **Avoid:** Layer mismatch **Prefer:** Visual approach matches chapter's pedagogical layer **L1 (Manual Foundation):** - Step-by-step diagrams - Concrete examples - Clear labeling (building vocabulary) **L2 (AI Collaboration):** - Before/after comparisons - Iteration flows - Three Roles Framework INVISIBLE (no role labels) **L3 (Intelligence Design):** - Architecture diagrams - Reusable pattern illustrations **L4 (Spec-Driven):** - Specification → implementation flow - Component composition diagrams **Principle:** Visual design reinforces pedagogical approach --- ### Duplicate Prevention Protocol **Avoid:** Generating different prompts that produce the same visual **Prevent BEFORE generation:** 1. **Review existing visuals in chapter:** - List all `*.png` files in target chapter directory - Read corresponding `*.prompt.md` files - Identify visual patterns already used 2. **Validate prompt distinctiveness:** - Does this prompt's intent differ clearly from existing prompts? - Example conflicts to detect: - ❌ Timeline + Graph → Both might render as timeline - ❌ Architecture + Workflow → Both might render as hierarchy - ❌ Same metaphor, different names → Same visual result 3. **Differentiation strategy:** - Make visual type explicit in story ("GRAPH showing exponential growth" not just "showing growth") - Use distinct metaphors (cascade vs tree vs timeline vs curve) - Specify unique structural elements (2D axes vs linear flow vs hierarchical pyramid) **Detect AFTER generation (in image-generator):** - Visual comparison with existing chapter images - Prompt alignment check (does output match brief intent?) **Principle:** Prevention cheaper than rework --- ## Anti-Patterns **Never:** - Generate visuals without reading chapter-index.md first (skipping context) - Use pixel specifications, font sizes, coordinates in prompts (kills reasoning) - Assume knowledge not in prerequisites (prerequisite violation) - Create decorative visuals without learning objective (Principle 7 violation) - Apply same complexity to A2 and C2 students (proficiency mismatch) - Create prompts without checking for duplicate visual patterns (causes rework) **Even if it seems reasonable:** - Don't use Python examples in Part 3 (students don't know Python yet) - Don't create complex multi-step visuals for A2 (cognitive overload) - Don't specify "44pt Roboto Bold" (removes Gemini's judgment) - Don't skip distinctiveness validation "because they have different filenames" (names differ, visuals might not) --- ## Creative Variance You tend to default to comparison diagrams even with story-driven prompts. Vary visual types: - **Timeline progressions** (evolution over time) - **Multiplication cascades** (compound growth visualization) - **Hierarchical authority flows** (governance models) - **Transformation sequences** (before → after → impact) - **Conceptual metaphors** (abstract → concrete mapping) Match visual type to story, not habit. --- ## Post-Generation Reflection After batch completion, analyze systematically (Q8): **Success patterns:** - Quality gate performance (which caught most issues?) - Average iterations (efficiency indicator) - Time vs estimate (planning accuracy) **Failure analysis:** - Deferred visuals root causes (layout? spelling? concept mismatch?) - Guardrail gaps (what principle would have prevented this?) - Planning effectiveness (conflicts caught early vs missed?) **Continuous improvement:** - Pattern-based updates (not one-off fixes) - New guardrails from learnings - Prompt template refinements Document in: `history/visual-assets/reflections/chapter-{NN}-reflection.md` **Principle:** Systematic reflection → Improved future performance --- ## Success Indicators You'll know this skill is working when: - ✅ Zero pixel specifications in prompts (creative briefs only) - ✅ Strategic plan created before visual analysis (Q0 complete) - ✅ Proficiency conflicts detected early (A2 limits enforced) - ✅ Prerequisite violations prevented (no unknown concepts) - ✅ Story/Intent/Metaphor in every prompt (reasoning activated) - ✅ Token conservation applied in batch mode (60-70% reduction) - ✅ Duplicate prevention validation passed (zero duplicate visuals) - ✅ Visuals feel distinctive and compelling (not generic PowerPoint) - ✅ Reflection document created after batch (systematic learning) **Result:** Professional-quality visuals that teach effectively, generated efficiently through planning, with zero duplicates requiring rework.