Marketing Os Starter

Marketing OS Starter

Skill by ara.so — Marketing Skills collection.

What It Does

Marketing OS Starter is a complete AI marketing team built for Claude Code. It includes 4 specialized agents (Orchestrator, Researcher, Strategist, Copywriter), 5 marketing skills, and battle-tested frameworks that turn research into creative briefs into finished copy — all with persistent memory that compounds across sessions.

The system runs on structured agent handoffs (JSON schemas), enforces brand voice automatically, and applies proven frameworks like the 6 Hook Formulas and BOFU Domination to every piece of output.

Installation

# Clone the repository
git clone https://github.com/ericosiu/marketing-os-starter.git my-marketing-os
cd my-marketing-os

The project structure:

marketing-os-starter/
├── CLAUDE.md                    # Main context file - your agency priorities
├── .claude/
│   ├── agents/marketing-os/     # 4 specialist agents
│   │   ├── orchestrator.md
│   │   ├── researcher.md
│   │   ├── strategist.md
│   │   └── copywriter.md
│   ├── skills/                  # 5 marketing skills
│   │   ├── research.md
│   │   ├── campaign-brief.md
│   │   ├── copywriting.md
│   │   ├── social-content.md
│   │   └── email-sequence.md
│   └── rules/                   # Intent routing
│       └── proactive-marketing.md
├── brands/                      # Agency + client brand files
│   └── your-agency/
│       ├── BRAND.md
│       ├── voice.md
│       └── clients/
├── memory/                      # Persistent memory
│   └── marketing-os/
│       ├── brand-voice.md
│       ├── campaign-history.md
│       ├── marketing-wisdom.md
│       └── working.md
├── schemas/                     # JSON contracts for handoffs
│   ├── audience-profile.json
│   ├── creative-brief.json
│   └── copy-deliverable.json
└── examples/                    # Sample outputs

Initial Configuration

1. Configure CLAUDE.md

This is the brain of your system. Claude reads it at the start of every session.

# Your Agency Context

**Agency**: [Your Agency Name]
**Primary Service**: [What you do]

## Priorities (Next 12 Months)

1. [Priority 1]
2. [Priority 2]
3. [Priority 3]

## Standards

**Minimum ROI Bar**: [X]x ROAS or [Y]% conversion lift
**Never Accept**: "Awareness" campaigns without revenue tracking

## Client Portfolio

- **[Client Name]**: [Brief description]
- **[Client Name]**: [Brief description]

2. Set Up Your Agency Brand

Edit brands/your-agency/BRAND.md:

# [Your Agency Name]

## Overview
[2-3 sentence value proposition]

## What We Do
- [Service 1]
- [Service 2]
- [Service 3]

## Public Client Examples
- [Client success story 1]
- [Client success story 2]

Edit brands/your-agency/voice.md:

# Voice Guidelines

## Tone
- Direct and data-driven
- No jargon or corporate speak
- Numbers over adjectives

## Always Use
- Specific metrics (e.g., "3.4x ROI" not "great results")
- Active voice
- Short sentences

## Never Use
- leverage, synergize, value-add, paradigm
- "excited to announce"
- Corporate platitudes

## Examples That Nail Our Voice

### Good
"We cut their CAC from $847 to $312 in 6 weeks. Here's the breakdown."

### Bad
"We're excited to share that our innovative approach helped drive meaningful results."

3. Add Your First Client

Copy the example client template:

cp -r brands/your-agency/clients/example-client brands/your-agency/clients/acme-corp

Edit brands/your-agency/clients/acme-corp/BRAND.md:

# Acme Corp

## Company Overview
- **Industry**: [SaaS/E-commerce/etc]
- **Target Market**: [B2B/B2C, company size, role]
- **Product**: [What they sell]

## Voice
[How this specific client speaks - may differ from agency voice]

## Past Campaigns
None yet.

Key Commands and Workflows

Running a Complete Campaign Pipeline

Start Claude Code and describe your need naturally:

"I need to promote Acme Corp's new analytics feature to marketing directors at B2B SaaS companies. Budget $5K, 45-day timeline."

The Orchestrator will automatically:

1. Invoke Researcher → produces audience-profile.json
2. Invoke Strategist → produces creative-brief.json
3. Invoke Copywriter → produces finished copy

Manual Skill Invocation

You can also call skills directly:

/research
Target audience: Marketing directors at B2B SaaS companies (50-500 employees)
Focus: Pain points around marketing attribution

/campaign-brief
Audience: [reference research output]
Goal: 30 demo requests
Timeline: 45 days
Budget: $5K

/copywriting
Brief: [reference brief output]
Deliverables: 5 LinkedIn posts, 1 landing page hero

/social-content
Topic: Marketing attribution mistakes
Platform: LinkedIn
Quantity: 5 posts
Target: Marketing directors

/email-sequence
Type: Nurture sequence
Segment: Ghost users (signed up, 0 actions)
Length: 5 emails over 2 weeks
Goal: First dashboard connection

Agent Handoff Pattern

Agents communicate through structured JSON. Example flow:

Researcher Output (memory/marketing-os/campaigns/acme-q2/audience-profile.json):

{
  "target_audience": {
    "role": "Marketing Director",
    "company_size": "50-500 employees",
    "industry": "B2B SaaS"
  },
  "pain_points": [
    {
      "pain": "Attribution reporting takes 2-3 days to compile",
      "evidence": "14 Reddit posts in r/marketing, 23 G2 reviews",
      "quote": "I spend more time building reports than reading them"
    }
  ],
  "voice_of_customer": {
    "actual_phrases": [
      "I spend more time building reports than reading them",
      "My CEO thinks marketing is a cost center because I can't prove otherwise"
    ]
  }
}

Strategist Reads the audience profile and outputs (creative-brief.json):

{
  "campaign_name": "Acme Attribution Fix",
  "core_message": "Stop spending 2 days building reports. See real-time attribution in 15 minutes.",
  "proof_points": [
    "14 Reddit posts confirm this pain point",
    "Average time saved: 2.3 days per month"
  ],
  "growth_playbook": "Playbook 6: Marketing Mistakes Content",
  "hook_formula": "Harsh Reality",
  "deliverables": {
    "landing_page_hero": 1,
    "linkedin_posts": 5,
    "email_sequence": 3
  }
}

Copywriter Reads the brief and produces final copy with the selected hook formula applied.

Working with Memory Files

Campaign History

After each campaign, the Strategist logs results to memory/marketing-os/campaign-history.md:

## Campaign: Acme Attribution Fix
- **Date**: 2026-05-15
- **Channel**: LinkedIn + Landing Page
- **Result**: 47 demo requests, 12 closed deals
- **What Worked**: "Harsh Reality" hook + specific time-saved stat
- **What Didn't**: Generic "learn more" CTA underperformed vs "See your attribution now"

This memory prevents repeating failed approaches and reinforces what works.

Brand Voice Evolution

As you approve copy, add winning examples to memory/marketing-os/brand-voice.md:

## Approved Headlines (2026-05)

### Hook: Harsh Reality
"Harsh reality: your marketing attribution is lying to you."
- **Campaign**: Acme Q2
- **Performance**: 8.2% CTR (2.3x average)

### Hook: Contrarian Challenge
"Everyone says 'just pick an attribution model.' That's surface-level thinking."
- **Campaign**: Acme Q2
- **Performance**: 6.7% CTR

After 5-10 campaigns, the Copywriter matches your voice without explicit direction.

Task Queue

memory/marketing-os/working.md tracks the current pipeline:

# Current Tasks

## In Progress
- [ ] Acme Q2 Campaign - waiting for client approval on headlines
- [ ] Research for DataPulse competitive analysis

## Blocked
- [ ] Email sequence for Acme - need segment data from client

## Completed This Week
- [x] Landing page copy for Acme Attribution Fix
- [x] 5 LinkedIn posts for Acme Q2

You can resume exactly where you left off in any session.

Real Usage Examples

Example 1: Full Campaign from Scratch

User: "Build a campaign to get 30 demo requests for Acme's new attribution feature. Target marketing directors at B2B SaaS companies, budget $5K, 45 days."

Orchestrator: Detecting new campaign request. Invoking full pipeline.

[Researcher produces audience-profile.json with 87 data points]

Strategist: Reading audience profile... Core pain point identified: "2-3 days per month wasted on attribution reports."

[Strategist produces creative-brief.json selecting Growth Playbook #6 and Harsh Reality hook]

Copywriter: Reading creative brief... Applying Harsh Reality hook formula.

[Copywriter produces 5 LinkedIn posts, 1 landing page hero, 3-email sequence]

Orchestrator: Campaign deliverables ready. Files saved to memory/marketing-os/campaigns/acme-q2/.

Example 2: Research Only

User: "Who should we target for a marketing attribution tool?"

[Orchestrator detects research intent, invokes Researcher]

Researcher: Conducting BOFU-first research...
- Analyzing search intent for "best marketing attribution tool"
- Scraping G2 reviews for voice-of-customer quotes
- Cross-referencing Reddit r/marketing pain points

[Produces audience-profile.json with job titles, pain points, actual quotes]

Example 3: Writing with Existing Brief

User: "Write 5 LinkedIn posts using the Acme Q2 brief."

[Orchestrator detects copywriting intent with existing brief, invokes Copywriter]

Copywriter: Reading brief at memory/marketing-os/campaigns/acme-q2/creative-brief.json...
- Hook formula: Harsh Reality
- Proof point: "2.3 days saved per month"
- Voice check: Loading brands/your-agency/clients/acme-corp/voice.md

[Produces 5 posts, each with different hook formula variation]

Configuration Reference

Agent Roles

Skill Triggers

The proactive routing system in .claude/rules/proactive-marketing.md auto-detects:

• Research triggers: "who's our audience", "competitive landscape", "pain points"
• Brief triggers: "plan a campaign", "what should we say", "strategy"
• Copy triggers: "write copy", "landing page", "headline"
• Social triggers: "LinkedIn post", "tweet", "social content"
• Email triggers: "drip campaign", "welcome sequence", "nurture"

Framework Reference

All frameworks live in memory/marketing-os/marketing-wisdom.md:

6 Hook Formulas:

1. Observation + Stat: "I analyzed 500 landing pages. 89% make the same mistake."
2. Contrarian Challenge: "Everyone says X. That's surface-level thinking."
3. Harsh Reality: "Harsh reality: your approach is costing you $X."
4. Personal Limitation: "I used to believe X. Then I ran the numbers."
5. Social Proof: "I sat in on 12 board meetings. Same scene every time."
6. Simple Declarative: "Your attribution is broken. Here's why."

7 Growth Playbooks (abbreviated):

• Playbook 1: Free Tool Flywheel
• Playbook 2: LLM Citation Strategy
• Playbook 3: Vertical Domination
• Playbook 6: Marketing Mistakes Content (3-5x engagement)
• Playbook 7: Data Network Effects

Common Patterns

Pattern: Multi-Client Agency Setup

brands/
├── your-agency/
│   ├── BRAND.md          # Your agency brand
│   ├── voice.md          # Your agency voice
│   └── clients/
│       ├── acme-corp/
│       │   ├── BRAND.md
│       │   └── voice.md  # May differ from agency voice
│       ├── techstart/
│       │   ├── BRAND.md
│       │   └── voice.md
│       └── dataflow/
│           ├── BRAND.md
│           └── voice.md

When starting a campaign, specify the client:

"Build a campaign for Acme Corp's new feature..."

The Orchestrator will load brands/your-agency/clients/acme-corp/ context automatically.

Pattern: Testing with Example Brand

The repo includes a complete fictional agency:

brands/example-agency/
├── BRAND.md              # GrowthLab (fictional agency)
├── voice.md
└── clients/
    └── datapulse/        # DataPulse (fictional SaaS client)
        ├── BRAND.md
        └── voice.md

Test the full pipeline before setting up your own brand:

"Build a campaign for DataPulse targeting marketing directors at mid-market SaaS companies."

Pattern: Voice Evolution Loop

1. Generate copy with current voice guidelines
2. Review and edit to match your actual voice
3. Log approved examples to memory/marketing-os/brand-voice.md
4. Repeat — the Copywriter learns from approved examples

After 5-10 campaigns, the voice matching becomes automatic.

Troubleshooting

Issue: Generic output despite brand voice file

Problem: Copy doesn't match your voice, sounds generic.

Solution:

1. Check brands/your-agency/voice.md has specific examples (not just rules)
2. Add 2-3 "Good vs Bad" examples showing your voice clearly
3. Add winning headlines to memory/marketing-os/brand-voice.md

## Examples That Nail Our Voice

### Good
"We cut their CAC from $847 to $312 in 6 weeks. Here's the breakdown."

### Bad
"We're excited to share that our innovative approach helped drive meaningful results."

Issue: Agent doesn't invoke the right skill

Problem: You ask for research but get copy instead.

Solution: The proactive routing in .claude/rules/proactive-marketing.md may need more trigger phrases. Add your common phrasing:

## Research Triggers
- "who should we target"
- "what do they care about"
- "audience analysis"
- [ADD YOUR PHRASE HERE]

Or invoke skills manually: /research instead of relying on auto-detection.

Issue: Handoff breaks between agents

Problem: Strategist can't find Researcher output.

Solution:

1. Check that Researcher saved output to memory/marketing-os/campaigns/[campaign-name]/
2. Verify JSON schema matches schemas/audience-profile.json
3. Manually reference the file:

"Create a brief using the research at memory/marketing-os/campaigns/acme-q2/audience-profile.json"

Issue: Campaign history not influencing new campaigns

Problem: Strategist repeats a failed approach.

Solution: Ensure memory/marketing-os/campaign-history.md has clear "What Worked / What Didn't" sections:

## Campaign: Acme Q1 Email Sequence
- **What Didn't Work**: Generic "Learn more" CTA → 1.2% CTR
- **Lesson**: Use specific action CTAs ("See your dashboard now" → 4.8% CTR)

The Strategist reads this file before creating new briefs.

Issue: Memory files getting too large

Problem: campaign-history.md or brand-voice.md becomes unwieldy after 50+ campaigns.

Solution: Archive old campaigns quarterly:

# Create archive
mkdir -p memory/marketing-os/archive/2026-q1

# Move old campaign data
mv memory/marketing-os/campaigns/acme-q1 memory/marketing-os/archive/2026-q1/

# Keep only last 10 campaigns in campaign-history.md
# Move older entries to archive/campaign-history-2026-q1.md

Advanced: Adding Custom Skills

To add a new skill (e.g., /paid-ads):

1. Create .claude/skills/paid-ads.md
2. Define the skill structure:

---
name: paid-ads
description: Generate paid advertising strategy and ad copy
triggers:
  - "create paid ads"
  - "facebook ads"
  - "google ads campaign"
---

# Paid Ads Strategy

## What This Skill Does
[Description]

## Inputs Required
- Campaign brief (from Strategist)
- Budget and timeline
- Target platform (Meta, Google, LinkedIn)

## Outputs
- Platform-specific ad copy
- Targeting recommendations
- Budget allocation

## Process
[Step-by-step]

3. Add trigger phrases to .claude/rules/proactive-marketing.md
4. Create a schema if needed: schemas/paid-ads-plan.json

The Orchestrator will automatically detect and route requests.

Integration with MCP Servers

To connect live data sources:

Google Analytics (GA4):

# Install GA4 MCP server (example - adjust to actual implementation)
npm install -g @mcp/google-analytics

# Add to Claude configuration
# Reference in CLAUDE.md: "GA4 data available via MCP"

Then in research:

"Pull last 30 days of campaign data from GA4 for Acme Corp."

HubSpot CRM:

# Install HubSpot MCP server
npm install -g @mcp/hubspot

# Reference contact segments in research
"Get email engagement data for Ghost Users segment from HubSpot."

The Researcher and Strategist can query live data instead of relying solely on manual input.

Start using Marketing OS: Open Claude Code in your marketing-os-starter directory and describe your first campaign. The system handles the rest.