Design system gtm
205 production GTM agent skills for Claude Code — sales, outbound, prospecting, RevOps, ABM, PLG, CS, automation. Framework-cited playbooks with artifacts + QA scripts.
npx -y skills add LeadMagic/gtm-skills --skill design-system-gtmAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
What its author says it does
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Define brand-context for AI agents — visual identity systems, voice/tone guides, color palettes with hex/RGB/HSL, typography systems with font stacks and type scales, logo usage rules, asset templates, and brand guardrails. Use when creating a design system for AI-generated GTM content, ensuring brand consistency across agent outputs, or implementing Google DESIGN.md specification. Includes Claude Code design patterns via claude-design skill.
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SKILL.md
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Design System for GTM
Overview
When AI agents generate sales collateral, pitch decks, one-pagers, social graphics, and emails, they need a brand system to reference. Without it, every output has different colors, different fonts, different voice — and your brand erodes across every customer touchpoint. This skill defines a complete AI-consumable design system with visual identity, voice/tone, templates, and guardrails. Designed to be read by both humans and AI agents.
Authoritative Foundations
- Google DESIGN.md Specification — Shapes deliverables for this skill — When AI agents generate sales collateral, pitch decks, one-pagers, social graphics, and emails, they need a brand system.
- Stitch 9-Section Brand Format — Shapes deliverables for this skill — When AI agents generate sales collateral, pitch decks, one-pagers, social graphics, and emails, they need a brand system.
- Brad Frost — Atomic Design — Atomic Design
- Nathan Curtis — Design System Monorepo Architecture — Design System Monorepo Architecture
- Dan Mall — Design System Governance — Design System Governance
When to Use
Trigger phrases: "create a design system for our AI-generated content", "define our brand for agents", "build a brand guide for sales materials", "ensure consistent voice across AI outputs", "DESIGN.md specification", "design tokens for agents", "AI brand system", "brand context for Claude"
Step-by-Step Process
Phase 1: Visual Identity System
Color Palette — must include hex, RGB, and HSL:
PRIMARY PALETTE
Primary: #0066FF rgb(0,102,255) hsl(216,100%,50%)
Primary Dark: #0044CC rgb(0,68,204) hsl(220,100%,40%)
Primary Light: #3388FF rgb(51,136,255) hsl(216,100%,60%)
SECONDARY / ACCENT
Accent: #FF6600 rgb(255,102,0) hsl(24,100%,50%)
NEUTRALS
Ink (text): #1A1A2E rgb(26,26,46) hsl(240,28%,14%)
Muted Text: #6B7280 rgb(107,114,128) hsl(220,9%,46%)
Surface: #FFFFFF
Background: #F9FAFB
Border: #E5E7EB
SEMANTIC
Success: #10B981 rgb(16,185,129) hsl(160,84%,39%)
Warning: #F59E0B rgb(245,158,11) hsl(37,92%,50%)
Danger: #EF4444 rgb(239,68,68) hsl(0,80%,60%)
Info: #3B82F6 rgb(59,130,246) hsl(217,91%,60%)
CSS Variable Output (for agents generating HTML/CSS):
:root {
--color-primary: #0066FF;
--color-primary-dark: #0044CC;
--color-primary-light: #3388FF;
--color-accent: #FF6600;
--color-ink: #1A1A2E;
--color-muted: #6B7280;
--color-surface: #FFFFFF;
--color-bg: #F9FAFB;
--color-border: #E5E7EB;
--color-success: #10B981;
--color-warning: #F59E0B;
--color-danger: #EF4444;
}
Typography System:
HEADINGS: Inter (Google Fonts)
H1: 48px / 1.1 line-height / 700 weight / letter-spacing: -0.02em
H2: 36px / 1.2 / 600 / -0.01em
H3: 24px / 1.3 / 600 / 0
H4: 20px / 1.3 / 600 / 0
BODY: Inter
Body L: 18px / 1.6 / 400
Body: 16px / 1.6 / 400
Body S: 14px / 1.5 / 400
Caption: 12px / 1.5 / 400
MONOSPACE (code, data): JetBrains Mono
Code: 14px / 1.5 / 400
CSS:
@import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap');
font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif;
Spacing Scale (8px base): 4, 8, 12, 16, 24, 32, 48, 64, 96, 128
Border Radius:
- Buttons, inputs: 8px
- Cards: 12px
- Modals: 16px
Shadows:
- Card: 0 1px 3px rgba(0,0,0,0.08)
- Elevated: 0 4px 12px rgba(0,0,0,0.1)
- Modal: 0 8px 32px rgba(0,0,0,0.12)
Phase 2: Voice and Tone Guide
Brand Voice Attributes (5 — be specific, not vague):
- Direct — no hedging, no "we believe," no "it could be argued." Say the thing.
- Data-backed — every claim has a number or source. "Most teams" → "73% of teams."
- Opinionated — take positions. "We recommend X, not Y" not "There are several approaches."
- Concrete — "47% reply rate" not "industry-leading engagement."
- Confident but not arrogant — "Here's what works" not "We're revolutionizing."
Tone by Context:
| Context | Tone | Example |
|---|---|---|
| Sales deck | Confident, data-heavy | "Teams using our platform see 47% reply rates within 30 days." |
| Case study | Narrative, specific | "Acme Corp was losing $2.3M/year to churn. Here's how they fixed it." |
| Email nurture | Helpful, low-pressure | "I noticed you downloaded our ROI calculator. Here are 3 ways customers use it." |
| Error messages | Clear, apologetic, helpful | "That didn't work. Here's why and how to fix it." |
| Social media | Punchy, shareable | "Stop guessing your ICP. Start scoring it." |
Banned Words and Phrases:
- "Revolutionary," "high-impact," "disruptive" (vague, overused)
- "Best-in-class," "industry-leading" (meaningless without data)
- "Synergize," "leverage" (as a verb), "holistic" (jargon)
- "We're excited to announce" (nobody cares if you're excited)
- Passive voice: "Results were achieved" → "We achieved results"
Preferred Language Patterns:
- Active voice always. "We built" not "It was built."
- Present tense. "The platform processes" not "The platform will process."
- Short sentences. Under 25 words when possible.
- Bullets over paragraphs in decks and one-pagers.
Phase 3: Asset Templates
Slide Master Template:
- 16:9 aspect ratio
- Header: Inter 36px, primary color, left-aligned
- Body: Inter 18px, ink color
- Footer: company logo (bottom-right), slide number (bottom-left), 12px muted
- Data slides: charts in primary + accent palette, no decorative elements
One-Pager Template:
- A4/US Letter
- Header: logo + product name
- Hero: value prop (H2), one-line description, hero image
- Body: 3-column feature grid
- Social proof: 3 customer logos + 1 testimonial
- CTA: prominent button/contact info
- Footer: company info, legal
Email Signature:
[First Name] [Last Name]
[Title] | [Company Name]
[Phone] | [Website]
[Calendly link]
[Company logo — 80px wide]
Data Visualization Style:
- Primary + neutral palette (limit to 5 data colors)
- No 3D charts, no pie charts (use bar/line/scatter)
- Direct labels (no legends when possible)
- Source line: "Source: [name], [date]" in 10px muted
Phase 4: Brand Guardrails
Always Acceptable (AI can generate without review):
- Social graphics using brand colors, typography, and voice
- Email copy following tone guidelines
- Blog post drafts (human reviews before publishing)
- Data visualizations in brand style
- Landing page sections following template
Requires Human Review:
- Customer-facing decks (check data accuracy)
- Pricing pages (legal/commercial review)
- Press releases (legal review)
- Customer quotes/testimonials (customer approval)
- Any content referencing specific customers
Never Allowed:
- Competitive claims without cited sources
- Revenue/growth numbers not publicly disclosed
- Customer names without explicit permission
- Guarantees or promises ("100% deliverability")
- Any content that implies endorsement by a named authority
Integration with Claude Code Design
When using Claude Code to generate branded assets, load this skill alongside
claude-design and popular-web-designs:
1. claude-design → drives the design process and artifact creation
2. design-system-gtm (this skill) → provides brand tokens and rules
3. popular-web-designs → provides visual vocabulary from known brands
The agent should output CSS variables matching this design system's tokens and follow the voice/tone guidelines for any copy it generates.
Output Format
DESIGN SYSTEM — [Company Name]
File: DESIGN.md (version controlled in repo)
Sections:
1. Brand Overview (2-3 sentence positioning)
2. Visual Identity (colors, typography, spacing, radii, shadows)
3. CSS Variable Output (copy-paste ready)
4. Voice and Tone (attributes, per-context, banned words)
5. Asset Templates (slide, one-pager, email, social, data viz)
6. Brand Guardrails (acceptable / review / never)
7. AI Agent Usage (how agents should reference this system)
Implementation Checklist
- All colors have hex, RGB, and HSL values
- CSS variable block is copy-pasteable into any project
- Typography includes Google Fonts import URL and font stack
- Voice attributes are specific and testable ("direct" > "professional")
- Banned words list exists (10+ entries)
- Tone guide covers at least 5 contexts
- Asset templates include specific dimensions and specs
- Guardrails have 3 clear tiers (always acceptable / review / never)
- AI agent usage instructions included (how to reference, what to load)
- File is version-controlled and linked from README
Quality Check
Before delivering, verify:
- Output matches the user's stated request
- Named frameworks or sources are reflected in the recommendation
- The deliverable is specific enough for an agent to execute
- Any assumptions, risks, or dependencies are explicit
- No unsupported claims, invented facts, or private/internal references are included
Common Pitfalls
-
Vague voice guidelines. "Professional and friendly" is useless. Agents need specific, testable attributes: "Short sentences. Active voice. No passive constructions. Data before adjectives." Fix: For each voice attribute, provide 3 examples of "this, not that."
-
RGB without hex. AI agents reference hex codes for HTML/CSS generation. Including RGB is good. Including only RGB is not. Fix: Hex is the primary color format for agents. RGB and HSL are supplementary.
-
No CSS variable output. Agents generating HTML need copy-pasteable CSS. Wading through a color palette table to extract hex codes produces errors. Fix: Include a
:root {}CSS block with all design tokens. -
Ignoring dark mode. Many agent-generated artifacts (dashboards, presentations) look different in dark mode. Fix: Include dark mode color variants or document that the brand is light-mode-only.
-
No guardrails. Without explicit rules, agents will improvise — and sometimes generate content that's off-brand, legally risky, or factually wrong. Fix: Clear tiered guardrails: acceptable, review, never.
-
Design system as PDF. If your design system is a Figma file or PDF, AI agents can't read it. Fix: DESIGN.md in markdown, version controlled, linked from all agent configuration files.
Execution Artifacts
references/framework-notes.md— named frameworks, citation anchors, and operating assumptionstemplates/output-template.md— copy-paste deliverable structure for the userscripts/check-output.py— local checklist validator for required sections This skill includes lightweight artifacts the agent can load on demand: Use the artifacts when the user asks for an implementation-ready deliverable, a repeatable workflow, or a quality check rather than generic advice.
Related Skills
claude-design— Design process for one-off HTML artifactspopular-web-designs— 54 known-brand design systems for visual vocabularydesign-system-builder— Build complete design systems from referencesbrand-kit— Logo design, color palette, typography, asset templatesui-ux-gtm— Landing pages, forms, signup flows, dashboardseffective-ui-design— Professional UI design guidelines