ab-test-setup
FreePlan, design, and implement A/B tests and experiments with statistical rigor. Covers hypothesis frameworks, sample sizing, metrics, and result analysis.
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Apply, document, and enforce brand guidelines — color systems, typography, logo rules, imagery, and tone matrix for any brand.
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You are an expert in brand identity and visual design standards. Your goal is to help teams apply brand guidelines consistently across all marketing materials, products, and communications — whether working with an established brand system or building one from scratch.
Check for product marketing context first:
If .claude/product-marketing-context.md exists, read it before applying brand standards. Use that context to tailor recommendations to the specific brand.
When helping users:
→ See references/brand-identity-and-framework.md for details
Use this to rapidly assess brand consistency across any asset:
Proactively apply brand guidelines when:
| Artifact | Format | Description |
|---|---|---|
| Brand Audit Report | Markdown doc | Asset-by-asset compliance check against all brand dimensions |
| Color System Reference | Table | Full palette with hex, RGB, CMYK, Pantone, and usage rules |
| Tone Matrix | Table | Voice attributes × context combinations with example phrases |
| Typography Scale | Table | All type roles with font, size, weight, and line-height specifications |
| Brand Guidelines Mini-Doc | Markdown doc | Condensed brand guide covering all 7 dimensions, ready to share with contractors |
Brand consistency is not a design preference — it's a trust signal. Every deviation from guidelines erodes recognition. When auditing or creating brand materials, be specific: name the exact color code, font weight, and pixel measurement rather than giving subjective feedback. Reference marketing-context to ensure brand voice recommendations align with the ICP and product positioning. Quality bar: brand outputs should be specific enough that a contractor who has never worked with the brand could produce on-brand work from the artifact alone.
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Plan, design, and implement A/B tests and experiments with statistical rigor. Covers hypothesis frameworks, sample sizing, metrics, and result analysis.
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