End-to-end content creation pipeline from research through editorial review to social distribution. Orchestrates a 3-stage workflow: research, draft/edit, and distribute. Supports blog posts, LinkedIn, Twitter threads, newsletters, and essays.
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End-to-end content creation pipeline: research, draft, review, distribute.
git clone https://github.com/thatrebeccarae/claude-marketing.git && cp -r claude-marketing/skills/content-workflow ~/.claude/skills/
Gather raw material for the content piece.
Output: Research brief with sources, data points, and recommended angle.
Create and refine the content.
Output: Polished draft ready for approval.
Adapt the finished piece for cross-platform distribution.
Output: Distribution pack with platform-specific adaptations.
/content-workflow [topic]
Runs all 3 stages: research → draft → review → distribute.
/content-workflow --from-draft [file path]
Skips research. Takes an existing draft through editorial review and distribution.
/content-workflow --distribute [file path]
Takes a finished, approved piece and creates the social distribution pack.
| Type | Research Depth | Draft Length | Distribution |
|---|---|---|---|
| Blog post | Deep (5+ sources) | 1,500-2,500 words | LinkedIn + Twitter + Email |
| LinkedIn post | Light (2-3 sources) | 150-300 words | Twitter adaptation only |
| Twitter thread | Light (1-2 sources) | 5-12 tweets | LinkedIn adaptation only |
| Newsletter | Medium (3-5 sources) | 500-1,000 words | Twitter + LinkedIn teasers |
| Essay | Deep (8+ sources) | 2,000-4,000 words | Full distribution pack |
Content moves through these statuses:
stub → draft → reviewed → approved → published → measured
↘ rejected (terminal)
For editorial review criteria and platform templates, see REFERENCE.md.
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A/B and multivariate testing methodology. Design experiments, calculate sample sizes, determine statistical significance, avoid common pitfalls, and interpret results. Platform-agnostic framework applicable to landing pages, emails, ads, pricing, and product features. Use when the user asks about A/B testing, split testing, experiment design, statistical significance, or conversion experiments.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Google and Meta paid media account structure evaluation. Audits campaign/ad set architecture against conversion volume minimums, budget thresholds, and targeting overlap. Identifies over-segmentation, under-segmentation, budget fragmentation, and structural anti-patterns blocking algorithmic learning. Provides consolidation roadmaps with migration plans. Use when inheriting accounts, quarterly health checks, or before scaling budgets.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) specialist. Optimize content and websites to appear in AI-generated answers from ChatGPT, Perplexity, Claude, Google AI Overviews, and other LLM-powered search experiences. Use when the user asks about AI search optimization, AEO, GEO, AI Overviews, appearing in AI answers, LLM citations, or optimizing for generative search.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Extract brand identity from a website URL — voice, colors, typography, imagery, values, and target audience — into a structured brand-profile.json. The profile feeds downstream skills (seo-content-writer, email-composer, frontend-design, pro-deck-builder, cross-platform-audit) for brand-consistent output. Use when the user says brand DNA, brand profile, extract brand, analyze brand, brand voice, brand identity, brand colors, or brand style guide.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Develop brand voice, tone matrices, messaging frameworks, and brand book documentation. Use when the user asks about brand voice, tone of voice, brand guidelines, messaging framework, or brand consistency.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Braze customer engagement platform expertise. Audit campaigns, Canvases, segments, messaging channels, and data architecture. Use when the user asks about Braze, customer engagement, push notifications, in-app messaging, cross-channel orchestration, or lifecycle marketing at scale.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.