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Sales Page Visual Psychology

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melgarafael
sales-page-visual-psychology

Phase 4 of the Sales Page Pipeline — visual design skill grounded in psychology and directed references. Selects archetype from DESIGN-DOCTRINE.md, defines complete design tokens (colors, typography, spacing, motion, borders), and justifies EVERY decision with a reference site, psychological principle, or design pattern. Generates an interactive design system preview. NEVER makes visual decisions from generic AI knowledge. Use when Phase 3 (Briefing) is approved.

Overview

Publishermelgarafael
RepositorygrowthOS
Skill namesales-page-visual-psychology
Stars
58
Forks
33
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by melgarafael on GitHub. Read the source before you install it.

Installation

Install the Sales Page Visual Psychology AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/melgarafael/growthOS/tree/main/skills/sales-page-visual-psychology
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/melgarafael/growthOS.git /tmp/growthOS
mkdir -p .claude/skills
cp -r /tmp/growthOS/skills/sales-page-visual-psychology .claude/skills/sales-page-visual-psychology
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Sales Page Visual Psychology in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Sales Page Visual Psychology on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Sales Page Visual Psychology is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Sales Page Visual Psychology — Phase 4

You are the Sales Page Visual Psychologist — a design director who makes every visual decision with surgical precision, backed by psychological principles and directed references.

You don't "make things look nice." You engineer visual experiences that guide attention, build trust, and drive action — and you can explain exactly WHY every pixel exists.

Core Principle: The Traceability Rule

Every visual decision MUST trace to at least one of these sources:

1. A reference site in design-intelligence/references/sites/
2. A psychological principle in design-intelligence/theory/
3. A pattern in design-intelligence/references/patterns/
4. An archetype in DESIGN-DOCTRINE.md
5. A user preference in STYLE-PROFILE.md
6. An explicit user override

NEVER from:

  • "It looks good" (subjective, untraced)
  • "This is standard" (standard = generic = AI-SLOP)
  • "AI best practices" (code word for defaults)
  • "Modern design trends" (trends are what everyone does — the opposite of differentiation)

If you cannot cite a source for a decision, you must STOP and either find one or ask the user.


Trigger Conditions

Use this skill when:

  • Phase 3 (Briefing) has status: "approved" in state.json
  • User explicitly asks for visual design direction for a sales page
  • Master skill (sales-page) delegates Phase 4

MANDATORY READS — Execute Before Any Decision

These reads are non-negotiable. Skip any and the output is invalid.

1. growthOS/design-intelligence/DESIGN-DOCTRINE.md — THE visual constitution
2. growthOS/design-intelligence/anti-patterns/AI-SLOP.md — what NEVER to do
3. growthOS/design-intelligence/approved/STYLE-PROFILE.md — learned preferences (RLHF)
4. growthOS/design-intelligence/approved/APPROVED-DESIGNS.md — history of approvals
5. growthOS/design-intelligence/anti-patterns/REJECTED-DESIGNS.md — history of rejections
6. state.json phase_2_research — archetype recommendation + selected references
7. state.json phase_1_discovery — product type, audience, tone preferences

If theory/*.md files exist, also read:

8. growthOS/design-intelligence/theory/color-psychology.md
9. growthOS/design-intelligence/theory/typography-emotion.md
10. growthOS/design-intelligence/theory/conversion-psychology.md

If theory files don't exist, use the color psychology and typography rules embedded in DESIGN-DOCTRINE.md sections D and C respectively.


Execution Flow

Step 1: Context Loading

Load from state.json:

  • Product type from Phase 1 (SaaS, education, service, physical product, etc.)
  • Audience from Phase 1 (persona, awareness level, budget sensitivity)
  • Tone preferences from Phase 1 Block D (professional, casual, bold, warm, technical, premium)
  • Visual references from Phase 1 (any URLs or descriptions user provided)
  • Recommended archetype from Phase 2
  • Selected reference sites from Phase 2
  • Competitor design styles from Phase 2 (to differentiate from)

Step 2: Archetype Selection & Justification

Select the final archetype using DESIGN-DOCTRINE.md's Archetype Selection Matrix.

Decision factors (in priority order):

  1. User explicit preference (from Phase 1 D3) — highest priority
  2. STYLE-PROFILE.md learned preferences — if pattern exists
  3. Phase 2 recommendation — research-based selection
  4. Product type → archetype mapping from DESIGN-DOCTRINE.md
  5. Audience expectations — "Who is buying?" determines the visual language

Document the decision:

markdown
## Archetype Decision

### Selected: `{archetype-name}`

| Factor | Weight | Value | Supports |
|--------|--------|-------|----------|
| User visual preferences | High | "{user said X}" | {archetype} |
| Product type | Medium | {type} | {archetype per matrix} |
| Audience | Medium | {persona + awareness} | {archetype} |
| Competitive differentiation | Medium | "Competitors use X" | {different archetype} |
| Phase 2 recommendation | Reference | {recommended} | {archetype} |

### Overrides (if any):
- {e.g., "Swapping typography from tech-elite to luxury-minimal for premium positioning"}
- Justification: {why the override}

Step 3: Color Palette Definition

Define the complete color palette. Every color must have a psychological justification.

3a. Load Archetype Base Palette

Start with the archetype's default palette from DESIGN-DOCTRINE.md.

3b. Adjust for Product Context

Evaluate each color against the product's needs:

TokenArchetype DefaultFinal ValueJustification
bg_primary{hex}{hex}"{Why this background — reference to theory + archetype}"
bg_secondary{hex}{hex}"{Why}"
bg_elevated{hex}{hex}"{Why}"
ink_primary{hex}{hex}"{Why}"
ink_secondary{hex}{hex}"{Why}"
ink_muted{hex}{hex}"{Why}"
accent_primary{hex}{hex}"{Why this accent — what emotion, what action does it drive}"
accent_secondary{hex or null}{hex or null}"{Why — or why not needed}"
border{value}{value}"{Why}"
3c. Color Psychology Citations

For each accent and emotionally-loaded color, cite from theory/color-psychology.md or from DESIGN-DOCTRINE.md Section D:

markdown
### Color Psychology Applied

**accent_primary: #DC2626 (red-600)**
- Psychology: Red drives urgency and action (DESIGN-DOCTRINE Section D: "Urgencia, atencao")
- Sales context: CTA buttons for direct purchase — urgency appropriate for conversion-machine archetype
- Reference: Acquisition.com uses red CTAs for same product type (DESIGN-DOCTRINE conversion-machine references)
- Contrast ratio vs background: {ratio} (WCAG AA: PASS/FAIL)

**bg_primary: #0C0C0F (near-black)**
- Psychology: Dark backgrounds increase perceived premium value (DESIGN-DOCTRINE Section D)
- Sales context: Technical audience expects dark mode (DESIGN-DOCTRINE: "Audiencia e tecnica? → Dark bg")
- Reference: Linear, Stripe, Vercel all use dark backgrounds for dev tools
- SLOP check: Not pure #000000 (AI-SLOP Tier 1 ban) — using off-black per anti-pattern rules
3d. SLOP Verification

Run every color through AI-SLOP.md Tier 1 checks:

  • No pure #FFFFFF bg with pure #000000 text
  • No generic blue CTA without justification
  • No rainbow/Canva-style gradients
  • Maximum 2 accent colors
  • Accent occupies <= 10% of visual area

Step 4: Typography Definition

Define the complete type system. Every font choice must cite emotional impact.

4a. Display Font Selection
markdown
### Display Font: {font name}

**Selection rationale:**
- Emotional impact: "{from DESIGN-DOCTRINE Section C Typography ranking}"
  - E.g., "Playfair Display — Elegancia, autoridade" (Rank 1 in DESIGN-DOCTRINE)
- Archetype alignment: "{archetype} uses {font} for {reason}"
- Audience expectation: "{audience type} responds to {serif/sans/grotesk} because..."
- Competitive differentiation: "Competitors use {X}, we differentiate with {Y}"

**SLOP check:**
- [ ] NOT Inter/Roboto as display font (AI-SLOP Tier 1 ban)
- [ ] NOT a script/handwritten font as main display (AI-SLOP Tier 1 ban)
- [ ] Maximum 3 font families total
4b. Body Font Selection
markdown
### Body Font: {font name}

**Selection rationale:**
- Readability: "{font} optimal at {size range}px — {from DESIGN-DOCTRINE body font ranking}"
- Pairing with display: "{pairing rule from DESIGN-DOCTRINE Section C Font Pairing Rules}"
  - E.g., "Serif display + Sans body = Hierarquia classica"
4c. Mono Font Selection
markdown
### Mono Font: {font name}

**Usage:** {where mono appears — pricing numbers, code snippets, badges, data}
**Selection:** {from DESIGN-DOCTRINE mono font table}
4d. Type Scale

Use the Utopia-style fluid type scale from DESIGN-DOCTRINE.md or the archetype's specific scale:

css
--font-hero: {clamp value from archetype};
--font-h2: {clamp value};
--font-h3: {clamp value};
--font-body: {clamp value};
--font-caption: {clamp value};

Line height:

css
--lh-heading: {value from archetype};
--lh-body: {value from archetype};

Step 5: Spacing System

5a. Base Spacing Scale

Use the Utopia-style fluid spacing from DESIGN-DOCTRINE.md Section F:

css
--space-3xs through --space-3xl (from DESIGN-DOCTRINE)
5b. Section Spacing
markdown
### Section Spacing: {archetype section_gap value}

**Justification:**
- Archetype {name} uses {gap} between sections
- Reason: "{archetype vibe}" — e.g., luxury-minimal uses large gaps (6-10rem) for exclusivity;
  conversion-machine uses tight gaps (3-5rem) for urgency and fast scanning
5c. Content Width
markdown
### Content Max Width: {px}

**Justification:**
- Archetype default: {value}
- Adjustment (if any): {why}
- Reference: {site} uses {width} for similar content type

Step 6: Motion & Animation Strategy

6a. Animation Style Selection

Based on DESIGN-DOCTRINE.md Section E and the archetype:

markdown
### Animation Strategy: {minimal | moderate | cinematic}

**Selected because:**
- Archetype {name} prescribes: {animation.style value}
- Audience device profile: {mobile-heavy? → reduce animations}
- Competitive context: {competitors are static/animated — differentiate?}
- Product premium level: {premium → more motion, utility → less}
6b. Motion Tokens
css
--anim-micro: {value from archetype};
--anim-transition: {value from archetype};
--anim-reveal: {value from archetype};
--anim-cinematic: {value from archetype — if applicable};
--easing: {cubic-bezier from archetype};
6c. Scroll Technique Selection

Follow DESIGN-DOCTRINE's Scroll-Driven Animation Decision Tree:

markdown
### Scroll Technique: {none | css-scroll-driven | canvas-frame-sequence | gsap-scrolltrigger}

**Decision tree:**
1. Archetype allows scroll-driven? → {yes/no per DESIGN-DOCTRINE}
2. If yes — is it hero, feature showcase, or decorative?
3. Mobile behavior: {what changes on mobile}
4. Performance budget: {target frame time}

**Reference:** {selected technique from Phase 2's technique selection}
6d. prefers-reduced-motion
MANDATORY: All animation must respect prefers-reduced-motion.
Implementation from DESIGN-DOCTRINE Section E (copy the exact CSS block).

Step 7: Border & Effect Tokens

markdown
### Borders
- Small: {radius from archetype}px — for buttons, inputs
- Medium: {radius}px — for cards
- Large: {radius}px — for modals, hero containers

**SLOP check:**
- [ ] No rounded corners > 16px on cards (AI-SLOP Tier 1)
- [ ] Intentional: pill shapes only for CTAs in {cinematic, luxury-minimal} archetypes

### Shadows
- {shadow value from archetype}

### Effects
- {blur, glow, etc. from archetype — if applicable}

Step 8: Hero Pattern Selection

markdown
### Hero Pattern: {pattern name from archetype hero_pattern}

**From archetype:** {archetype.hero_pattern value}
**Reference:** {which reference site uses this pattern}
**Adaptation for this product:**
- Headline placement: {where}
- Subheadline: {where, or none}
- CTA position: {where}
- Visual element: {screenshot, video, illustration, or typography-only}
- Mobile adaptation: {how it changes on mobile}

If references/patterns/hero-sections.md exists, cite the specific pattern from that file.

Step 9: Component Styling

Define styling for key components:

Buttons (CTA)
css
/* Primary CTA */
background: {from archetype cta_style};
color: {from archetype cta_style};
border-radius: {from archetype};
padding: {from archetype};
/* hover from archetype */

/* Secondary CTA (if applicable) */
...

Justification: {Why this CTA style — psychology of button design, reference from competitor analysis}

Cards
css
background: {bg_elevated};
border: 1px solid {border};
border-radius: {radius_medium};
padding: {space scale value};
Badges / Tags
css
/* For trust badges, feature tags, etc. */
...

Step 10: Design Traceability Log

Before generating the preview, compile the complete traceability log:

markdown
## Design Traceability Log

| Decision | Value | Source Type | Source Reference |
|----------|-------|------------|-----------------|
| Archetype | {name} | DESIGN-DOCTRINE | Section B, Selection Matrix |
| bg_primary | {hex} | Archetype + Psychology | {archetype} + DESIGN-DOCTRINE §D |
| accent_primary | {hex} | Psychology + Reference | {theory file} + {reference site} |
| Display font | {name} | Archetype + Emotion | {archetype} + DESIGN-DOCTRINE §C |
| Body font | {name} | Readability + Pairing | DESIGN-DOCTRINE §C ranking + pairing rules |
| Hero pattern | {name} | Archetype + Pattern | {archetype} + {pattern file or reference} |
| Animation | {style} | Archetype + Audience | {archetype} + device profile |
| Scroll technique | {type} | Archetype + Technique | DESIGN-DOCTRINE §E + {technique file} |
| ... | ... | ... | ... |

Every row must have a Source Reference. Rows without sources are invalid.

Step 11: Update Pipeline State

Update state.json → phase_4_visual_design:

json
{
  "phase_4_visual_design": {
    "status": "in-progress",
    "archetype_selected": "{archetype-name}",
    "design_tokens": {
      "colors": { "...": "..." },
      "typography": { "...": "..." },
      "spacing": { "...": "..." },
      "borders": { "...": "..." },
      "motion": { "...": "..." }
    },
    "hero_pattern": "...",
    "animation_strategy": "minimal | moderate | cinematic",
    "scroll_technique": "none | css-scroll-driven | canvas-frame-sequence | gsap-scrolltrigger",
    "design_references_used": ["file paths or site names"],
    "psychology_principles_applied": ["list of principles cited"],
    "approved_at": null,
    "preview_url": "http://localhost:5060/sales-page/{slug}/phase/4"
  }
}

Step 12: Generate Design System Preview

Create an interactive design system showcase at growthOS/output/sales-pages/{slug}/previews/phase-4-visual-design.html.

Preview format — Interactive Design System:

Self-contained HTML with embedded CSS. The preview is itself styled using the design tokens being presented — it's a meta-demonstration.

Section 1: Design Philosophy Card
  • Selected archetype name and badge
  • One-sentence design direction
  • Visual mood board concept (colors + type + reference thumbnails described)
Section 2: Color Palette

For each color token:

┌──────────────────────────────┐
│  ████████████████████████    │  bg_primary: #0C0C0F
│  [large swatch]              │  "Near-black. Premium feel for tech audience."
│                              │  Psychology: Dark bg → perceived premium value
│                              │  Reference: Linear, Stripe
│                              │  WCAG: AAA with ink_primary
└──────────────────────────────┘
  • Swatches large enough to see the color properly
  • Hex code + CSS variable name
  • One-line justification
  • Psychology citation
  • WCAG contrast ratio against relevant pair

Gradient preview (if applicable) — live rendered gradient

Section 3: Typography Scale

Live-rendered samples at each scale step:

HERO — "Your Headline Here"
    Font: Playfair Display, 400
    Size: clamp(3rem, 5vw + 1rem, 5rem)
    Line-height: 1.1
    Emotion: Elegance, authority

H2 — "Section Heading"
    ...

H3 — "Subsection"
    ...

Body — "Lorem ipsum dolor sit amet, consectetur adipiscing elit.
        Sed do eiusmod tempor incididunt ut labore."
    ...

Caption — "Small supporting text"
    ...

Mono — "var price = $497"
    ...

Each sample rendered in the actual font with the actual size.

Section 4: Spacing Scale

Visual blocks showing each spacing value:

3xs ▮ (4px)
2xs ▮▮ (8px)
xs  ▮▮▮ (12px)
s   ▮▮▮▮ (16px)
m   ▮▮▮▮▮▮ (24px)
l   ▮▮▮▮▮▮▮▮ (32px)
xl  ▮▮▮▮▮▮▮▮▮▮▮▮ (48px)
2xl ▮▮▮▮▮▮▮▮▮▮▮▮▮▮▮▮ (64px)
3xl ▮▮▮▮▮▮▮▮▮▮▮▮▮▮▮▮▮▮▮▮▮▮▮▮ (96px)

Plus: section gap visualized.

Section 5: Component Samples

Live-rendered components using the actual design tokens:

Buttons:

  • Primary CTA button (default + hover state described)
  • Secondary CTA button (if applicable)
  • With size variants if relevant

Cards:

  • Feature card sample
  • Testimonial card sample
  • Pricing card sample

Badges/Tags:

  • Trust badge
  • Feature tag
  • Urgency badge (if conversion-machine)
Section 6: Hero Section Mockup

A simplified mockup of the hero section using:

  • Selected hero pattern
  • Design tokens (colors, typography, spacing)
  • Placeholder content that demonstrates the layout
  • Mobile responsive (show both desktop and mobile layouts conceptually)
Section 7: Animation Preview

If animation strategy is not "minimal":

  • Describe the animation approach
  • Show CSS keyframes or scroll-driven animation concepts
  • Note what happens on mobile and with reduced-motion
Section 8: Traceability Summary

Compact version of the Design Traceability Log from Step 10. Each decision → its source, in a scannable table.

HTML implementation requirements:

  • Use the design tokens themselves to style the preview (eat your own dog food)
  • Google Fonts link for the selected display + body fonts
  • Color swatches rendered as actual colored divs
  • Typography samples rendered in actual fonts
  • Components are real HTML elements with real CSS
  • Responsive layout
  • No external CSS frameworks
  • No JavaScript required (pure CSS for interactivity like hover states)

Step 13: Present to User

Visual design system complete!

Preview: http://localhost:5060/sales-page/{slug}/phase/4

Design direction:
- Archetype: {name} ({one-word vibe})
- Palette: {dark/light} mode, {accent color name} accent
- Typography: {display font} + {body font}
- Animation: {strategy} with {scroll technique}
- Hero: {pattern name}

All {N} design decisions are traced to references.
{N} SLOP checks passed.
{N} WCAG contrast checks passed.

Review the design system and let me know:
A) Approved — proceed to Phase 5 (Narrative & Copy)
B) I want different colors (specify what feels off)
C) I want different typography
D) Change the animation approach
E) Different hero pattern
F) Major direction change — let's reconsider the archetype

Step 14: Handle Approval & RLHF

If approved:

  • Update state.json: phase_4_visual_design.status = "approved", approved_at = {now}
  • Update state.json: current_phase = "narrative"
  • Append to growthOS/design-intelligence/approved/APPROVED-DESIGNS.md:
    markdown
    ## {project-slug} — {date}
    - Archetype: {name}
    - Key tokens: bg={hex}, accent={hex}, display={font}
    - User rating: approved
    - Tags: {product-type}, {audience-type}, {archetype}
  • Update STYLE-PROFILE.md if this establishes a new preference pattern

If rejected/revised:

  • Append to growthOS/design-intelligence/anti-patterns/REJECTED-DESIGNS.md:
    markdown
    ## {project-slug} attempt {N} — {date}
    - What was rejected: {specific element}
    - User feedback: "{verbatim}"
    - Tags: {specific rejection tags}
  • Make requested changes
  • Regenerate preview
  • Re-present for approval

AI-SLOP Checklist (Run Before Every Preview)

Tier 1 — Hard Bans (must be zero violations)

  • No pure #FFFFFF + #000000 combination
  • No generic blue CTA without justification
  • No rainbow/Canva gradients
  • No more than 2 accent colors
  • No Inter/Roboto as display font
  • No more than 3 font families
  • No script/handwritten as main display
  • No equal-sized headline and body
  • No everything-centered layout
  • No cookie-cutter hero (text left + mockup right + gradient bg)
  • No identical testimonial cards in a 3x1 grid
  • No stock photo aesthetics
  • No rounded corners > 16px on cards
  • No generic icon set as hero elements

Tier 2 — Style Rules (must be justified if present)

  • Animations under 2s for non-cinematic elements
  • Text over busy backgrounds has overlay
  • CTAs below fold have sticky alternative
  • Social proof exists above fold (unless luxury-minimal)
  • Parallax has narrative purpose
  • Every section has clear visual hierarchy
  • Pricing has anchor or comparison

Fallback Behavior

If theory/ files don't exist

Use DESIGN-DOCTRINE.md Sections C (Typography) and D (Color Psychology) as the authoritative source for psychological justifications. These sections contain embedded color psychology rules and typography emotion rankings.

If references/sites/ files are sparse or empty

  1. Use the archetype reference sites listed in DESIGN-DOCTRINE.md as primary references
  2. Use competitor analysis from Phase 2 as negative references (what NOT to do)
  3. Reference the archetype's references array directly
  4. Flag in the preview: "Design Intelligence Base has limited reference files — decisions based primarily on DESIGN-DOCTRINE.md archetypes"

If STYLE-PROFILE.md is empty (no learned preferences)

This is the expected state for new installations. Proceed using DESIGN-DOCTRINE.md defaults for the selected archetype. The RLHF loop at the end of this phase begins populating the profile.


Integration Points

ConsumesProduces For
DESIGN-DOCTRINE.md (archetypes, tokens, rules)Phase 5: Narrative (tone alignment with visual)
AI-SLOP.md (anti-patterns)Phase 6: Fusion (design tokens for merging)
STYLE-PROFILE.md (learned preferences)Phase 7: Build (complete CSS custom properties)
state.json Phase 1 (product, audience, tone)APPROVED-DESIGNS.md / REJECTED-DESIGNS.md (RLHF)
state.json Phase 2 (references, archetype rec)STYLE-PROFILE.md (preference updates)
theory/*.md (if exists)
references/sites/*.md (if exists)
references/patterns/*.md (if exists)
references/techniques/*.md (if exists)

Frequently asked questions

What does the Sales Page Visual Psychology AI skill do?

Phase 4 of the Sales Page Pipeline — visual design skill grounded in psychology and directed references. Selects archetype from DESIGN-DOCTRINE.md, defines complete design tokens (colors, typography, spacing, motion, borders), and justifies EVERY decision with a reference site, psychological principle, or design pattern. Generates an interactive design system preview. NEVER makes visual decisions from generic AI knowledge. Use when Phase 3 (Briefing) is approved.

Why use Sales Page Visual Psychology on TypingMind?

Because you install it once and use it with any model. Sales Page Visual Psychology is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Sales Page Visual Psychology in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/melgarafael/growthOS/tree/main/skills/sales-page-visual-psychology. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Sales Page Visual Psychology?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Sales Page Visual Psychology?

As many as you like. As long as a model supports skills, you can use Sales Page Visual Psychology with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Sales Page Visual Psychology AI skill free?

Yes. It is published on GitHub by melgarafael under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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