happycapy-ai/happycapy-skills/world-class-carousel
Claude Code and agent skill by happycapy-ai/happycapy-skills
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Generate world-class Instagram carousel content on any topic. Produces 7-10 publication-ready slides (1080x1350) with AI-generated visuals, precise typography, Instagram music recommendations, optimized captions, and hashtags. Uses Aristotelian first-principles framework with 7 content archetypes, 6 hook patterns, a mandatory Bullshit Test quality gate, and a comprehensive design system. Fully generalized -- works for ANY topic. Triggers: instagram carousel, create carousel, carousel post, make carousel slides, instagram slides, carousel content, slide deck for instagram, swipeable post
Install
npx vskill@latest install happycapy-ai/happycapy-skills/world-class-carouselSKILL.md
World-Class Instagram Carousel Generator
Generate Instagram carousels that are genuinely world-class: content people save, share, and come back to. Not engagement bait. Not AI slop. Actual value, delivered through precise visual design and narrative structure.
This skill is fully generalized. It contains FORM (structure, principles, patterns), not MATTER (specific topics). The user provides the matter (topic); the skill provides the form (archetypes, design system, music matrix, quality gates). Together they produce the carousel. Nothing is hardcoded.
BEFORE YOU START: Read KNOWN_ISSUES.md
Before generating ANY carousel, read /home/node/.claude/skills/world-class-carousel/KNOWN_ISSUES.md. It contains compressed rules from all previous sessions -- data format gotchas, sizing rules, visual strategy decisions, and quality gates. Ignoring it means repeating solved mistakes.
EXECUTION PIPELINE
When the user requests a carousel, execute these 6 phases in order (Phase 6 runs post-delivery):
PHASE 1: RESEARCH & STRUCTURING
- Analyze the topic -- What is the core insight? What specific value can this deliver?
- Identify the audience -- What does the target audience NOT already know? What's their current understanding?
- Auto-detect content vertical and theme -- Use the Content Vertical Detection table below
- Select the archetype -- Which of the 7 carousel archetypes (see below) fits best? Use the Archetype Selection Guide below. Auto-select unless the user specifies.
- Design the narrative arc -- Map each archetype role to a renderer slide type using the Role-to-SlideType Mapping below. Ensure each slide creates a curiosity gap that the next slide resolves.
- Run the Bullshit Test on the outline -- Does every slide pass? (See QUALITY GATE below)
Content Vertical Detection (Topic -> Theme)
Analyze the topic and auto-select the renderer theme:
| Content Vertical | Keywords/Signals | Renderer Theme | Background Style | |
|---|---|---|---|---|
| Tech / AI / Coding | AI, code, developer, API, tools, stack, programming, SaaS, data | dark | gradient (default) | |
| Business / Strategy | growth, revenue, startup, founder, marketing, sales, strategy, scale | earth | gradient | |
| Education / How-To | learn, tutorial, guide, roadmap, beginner, master, course, how to | clean | gradient | |
| Creative / Design | design, UX, brand, visual, aesthetic, portfolio, creative | dark | gradient_mesh | |
| Mindset / Philosophy | mindset, habits, productivity, stoic, growth, mental, philosophy | warm | gradient |
If the user specifies a brand config with a theme, always use that instead.
Content Category Selection (10 Categories, Aristotelian)
Each category has unique visual DNA derived from psychology axioms (Cialdini, cognitive load theory, dual coding, serial position effect). Select based on topic:
| If the topic is about... | Category | Arc Shape | Hook Style | Primary Cialdini | |
|---|---|---|---|---|---|
| Explaining a research paper | paper_decoder | Revelatory | Face + paper panel | Authority | |
| Comparing AI tools/models | tool_showdown | Divergent | Multi-screenshot face-off | Social Proof | |
| Today's AI development | breaking_news | Convergent | News-editorial face | Scarcity | |
| Step-by-step AI tool how-to | tool_tutorial | Linear | Phone-in-hand / device mockup | Reciprocity | |
| Controversial opinion | hot_take | Confrontational | Bold abstract typography | Authority | |
| Copy-paste prompts/templates | prompt_playbook | Divergent | Phone screenshot mockup | Reciprocity | |
| Complete sector overview | industry_map | Divergent | Multi-person face-off | Authority | |
| Build [X] with AI project | build_this | Linear+Reveal | Multi-device result showcase | Social Proof | |
| Funding/business news | founders_money | Convergent | Founder portrait + data | Scarcity | |
| Future predictions/timeline | future_scenario | Revelatory | Abstract cinematic AI imagery | Scarcity |
Universal Psychology Rules (apply to ALL categories):
- Max 4 information chunks per slide (Cognitive Load Theory, Sweller)
- Pattern interrupt every 2-3 slides (diagram, comparison, color shift, or layout change)
- Density wave: H-M-H-M-H-H-M (never 3 high-density slides consecutively)
- Synthesis slide = THE save trigger (Serial Position Effect: last items remembered best)
- Dual-code the hardest concept (Paivio: visual + text = 6.5x retention)
- CTA matches save trigger: utility categories → "Save this", social categories → "Share/Comment"
Category-to-Slide-Sequence Quick Reference:
paper_decoder(9 slides): hook → body → diagram → body → body → diagram → body → synthesis → ctatool_showdown(8 slides): hook → body → comparison → body → body → comparison → synthesis → ctabreaking_news(8 slides): hook → body → body → body → diagram → body → synthesis → ctatool_tutorial(8 slides): hook → body → tool → tool → tool → body → synthesis → ctahot_take(7 slides): hook → body → body → body → body → synthesis → cta (text-driven, no diagrams)prompt_playbook(9 slides): hook → body → body → body → comparison → body → body → synthesis → ctaindustry_map(9 slides): hook → diagram → body → body → body → comparison → diagram → synthesis → ctabuild_this(8 slides): hook → body → tool → tool → tool → body → synthesis → ctafounders_money(7 slides): hook → body → body → body → diagram → synthesis → ctafuture_scenario(8 slides): hook → body → body → diagram → body → body → synthesis → cta
Role-to-SlideType Mapping
Map each archetype role to a renderer slide type when building the carousel spec:
| Archetype Role | Renderer Slide Type | Notes | |
|---|---|---|---|
hook | hook | Use title + title_highlight for split title effect | |
intro, context, reveal, before | body | Use title_highlight for the key phrase | |
step, component, layer, shift, evidence, action | body | Use bullets for key points | |
item | body | Use title_highlight for the item name, bullets for details | |
diagram, connection | diagram | Use diagram_nodes with vertical or horizontal layout | |
contrast, reframe | comparison | Use columns with opposing views | |
result, after, lesson, implication | body | Use title highlight to emphasize the key outcome | |
synthesis | synthesis | Use points[] for numbered key takeaways | |
cta | cta | Use handle, cta_text, optional stats[] | |
bonus, pitfalls, prediction | body | Use bullets for listed points |
PHASE 1.5: VISUAL STRATEGY DECISION (Before Writing Content)
Before writing any content, decide the visual strategy for this carousel. You have access to multiple tools -- choose the right ones for the topic.
Available Visual Tools Inventory
| Tool | What It Does | When to Use | How to Invoke | |
|---|---|---|---|---|
| AI Cinematic Images | HD photorealistic/artistic images (Gemini 3 Pro) | Hook/CTA backgrounds, emotional priming, conceptual anchoring | generate-image skill with hyper-detailed prompt (50+ words) | |
| AI Flowcharts/Diagrams | Production-quality flowcharts with text labels, arrows, boxes | Process flows, pipelines, decision trees -- REPLACES TikZ for better visuals | generate-image skill with structural prompt describing boxes + connections | |
| AI Architecture Diagrams | Blueprint-style system diagrams with components and connections | Microservices, tech stacks, system design | generate-image skill with component/connection prompt | |
| AI Infographics/Charts | Bar charts, data visualizations with accurate labels and proportions | Market data, statistics, comparisons | generate-image skill with data + style description | |
| AI Abstract Backgrounds | Neural networks, geometric patterns, cosmic visuals | Slide backgrounds via ai_bg | generate-image skill with atmosphere/material prompt | |
| TikZ Diagrams | Vector flowcharts in LaTeX (basic but reliable) | Simple 3-5 node flows where AI image gen is overkill | Use diagram slide type with diagram_nodes | |
| Gradient Backgrounds | TikZ-rendered gradient fills with geometric accents | Default for all text-only slides | Set bg_style: "gradient" in slide data |
CRITICAL: Slide-Type Visual Rule (Experimentally Verified)
This rule was established through controlled A/B experiments (7 strategies, same content, scored 1-10). It overrides gut instinct:
| Slide Type | Visual Strategy | WHY (Experimental Evidence) | |
|---|---|---|---|
| Hook | ai_bg full-bleed + 0.60-0.68 overlay | Scroll-stopping power. First slide = 80% of engagement. Score: 8.0/10 | |
| Body | TEXT-ONLY. No images. | Images on body slides destroy 40% of content space. Text-only scored 8.3/10 vs 5.7/10 with images | |
| Diagram | AI-generated diagram as `ai_bg` (preferred) OR TikZ fallback | Gemini 3 Pro generates production-quality flowcharts with readable labels, arrows, and boxes. Far more visually striking than basic TikZ. Use ai_bg + 0.55-0.65 overlay so text remains readable over the diagram. | |
| Synthesis | Text-only | Save-worthy reference material. Images would reduce information density. | |
| CTA | ai_bg full-bleed + 0.65-0.70 overlay | Emotional close with visual punch. |
DO NOT put AI images on body slides. This was the single biggest quality mistake found in testing. DO NOT use browser screenshots on any slides. They always look terrible embedded in carousel slides.
Visual Strategy Decision Matrix (Topic-Level)
For each topic, determine the primary visual mode, background style, and which slide-level visuals to use:
| Topic Type | Background Style | Hook Visual | Body Visuals | Diagram Strategy | Example | |
|---|---|---|---|---|---|---|
| Philosophy / Mindset | gradient | AI image: symbolic figure | None (text carries weight) | AI-generated concept map | Stoic principles: marble bust + storm | |
| Tool Review / SaaS | gradient or gradient_mesh | AI image: abstract tech glow | None (text-only bullets describe tools) | AI-generated comparison chart | "6 AI Tools": text descriptions + AI chart | |
| News / Current Events | gradient | AI image: dramatic scene | None (text with citations) | AI-generated timeline or power map | "AI War 2025": cinematic + AI power map | |
| Technical Tutorial | gradient (clean) | AI image: conceptual diagram | None (step-by-step text) | AI-generated architecture/flowchart | "Deploy with Docker": AI architecture diagram | |
| Business / Strategy | gradient | AI image: bold abstract | None (text with real data citations) | AI-generated bar chart or funnel | "Growth Hacking": AI infographic | |
| Comparison / Versus | gradient_mesh | AI image: abstract contrast | comparison slide type columns | AI-generated side-by-side chart | "React vs Vue": comparison columns + AI chart | |
| Creative / Design | gradient_mesh (dark) | AI image: artistic/gallery quality | None (text-only) | AI-generated process flow | "UX Trends 2025": artistic + AI flow | |
| Framework / Mental Model | gradient | AI image: system metaphor | None (text explains components) | AI-generated flowchart (preferred over TikZ) | "OODA Loop": AI flowchart as ai_bg | |
| Data / Research | gradient | AI image: data visualization concept | None (text with specific numbers) | AI-generated bar chart / infographic | "AI Market 2025": AI bar chart |
AI Image Generation Best Practices
This is the start of the file. Read the full SKILL.md on GitHub.
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/world-class-carousel/SKILL.md
Popularity
- Repository stars
- 137
- Repository forks
- 30
- 7-day trend score
- 25
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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