Multi-Client Ghostwriting Workspace

Overview

This is a comprehensive AI-powered content creation system designed for professional ghostwriters managing multiple clients. The system generates high-quality, platform-specific content across multiple channels while maintaining each client's unique brand voice and avoiding AI detection patterns.

Purpose

This workspace enables ghostwriters to efficiently manage unlimited clients within a single, organized system. Each client gets their own folder with brand guidelines, content rules, and output requirements, while universal writing standards ensure consistent quality across all accounts.

Project Structure

Multi-Client Workspace/
├── -workflow-rules/          # AI agent workflow automation
├── -writing-rules/           # Universal content creation guidelines
├── [client-name]/           # Individual client folders (create as needed)
│   ├── [month-year]/       # Monthly content organization by date
│   ├── brand.mdc           # Client's brand identity and voice
│   └── outputdoc.mdc       # Client's content requirements
└── README.md               # This file

How Client Folders Work

• Create a new folder for each client using their name or identifier
• Each client folder contains their unique brand guidelines (brand.mdc)
• Content requirements and posting schedule go in outputdoc.mdc
• Monthly subfolders organize completed content by date
• AI agents reference only the current client's folder to prevent voice contamination

Setting Up a New Client

Step 1: Create Client Folder Structure

1. Create a new folder named after your client (e.g., john-smith-coaching)
2. Inside the client folder, create:
   • brand.mdc - Client's brand identity, voice, tone, and positioning
   • outputdoc.mdc - Content requirements, posting schedule, and platform specifications
   • Monthly subfolders as content is created (e.g., 7-july-25/)

Step 2: Configure Brand Guidelines (brand.mdc)

Include these essential elements:

• Brand Name & Mission: What they do and why
• Voice & Tone: How they communicate (professional, casual, technical, etc.)
• Target Audience: Who they're speaking to
• Content Pillars: 3-5 main topics they cover
• Anti-Brand: What they explicitly are NOT
• Visual Style: Colors, fonts, imagery preferences

Step 3: Define Content Requirements (outputdoc.mdc)

Specify:

• Platform Mix: Which social platforms to focus on
• Posting Schedule: How often to post on each platform
• Content Types: Long-form vs short-form preferences
• Performance Goals: What success looks like
• File Naming Convention: How to organize the content files

Step 4: Content Strategy Framework

The system works best with this proven approach:

1. Test short-form content first (LinkedIn, Twitter) to gauge audience response
2. Analyze performance to identify resonating topics and formats
3. Expand winners into long-form content (YouTube, newsletters, blog posts)
4. Iterate and optimize based on engagement data

Key System Features

🤖 AI Detection Prevention

Advanced rules built into the global writing guidelines to create authentic, human-sounding content:

• Eliminates robotic contrast formats ("This isn't about X, it's about Y")
• Removes AI crutch phrases ("Let's dive deep into...")
• Uses natural conversation patterns and varied sentence structures
• Prevents formulaic content patterns that signal AI generation

📋 Client Isolation System

Strict separation prevents cross-client contamination:

• Each client folder operates as an isolated environment
• AI agents reference only the current client's brand guidelines
• No mixing of voices, styles, or content between clients
• Universal quality standards applied across all accounts

🎯 Platform Optimization

Built-in rules for major content platforms:

• LinkedIn: Professional formatting, character limits, engagement hooks
• Twitter/X: Thread-friendly structure, hashtag optimization, timing
• YouTube: Tutorial format guidance, SEO optimization
• Email/Newsletter: Subject lines, CTAs, personalization
• Blog/Long-form: Structure, headlines, readability

File Naming Convention

Content files follow a structured naming pattern (customizable per client):

• li-[topic].md - LinkedIn posts
• x-[topic].md - Twitter/X content
• yt-[topic].md - YouTube videos
• em-[topic].md - Email campaigns
• bl-[topic].md - Blog posts
• nl-[topic].md - Newsletter content

Note: Adapt naming conventions to match your client's preferences in their outputdoc.mdc file.

Daily Workflow for Ghostwriters

Content Creation Process

1. Select active client - Navigate to their folder
2. Review brand guidelines - Read brand.mdc for voice and positioning
3. Check content requirements - Reference outputdoc.mdc for today's needs
4. Apply platform rules - Use appropriate guidelines from -writing-rules/
5. Generate content - Create using AI agents with client-specific context
6. Quality check - Scan for AI detection patterns using global rules
7. Organize files - Save in appropriate monthly subfolder with correct naming

Workflow Automation

1. Weekly planning - Use content-calendar-generator.mdc for batch creation
2. Performance analysis - Tag high-performing content for future variations
3. Client isolation - Never reference other clients' content or styles
4. Consistency checks - Ensure each piece matches the client's established voice

AI Agent Instructions

How AI Should Use This Workspace

When generating content, AI agents should follow this hierarchy:

1. Global Rules First - Always reference -writing-rules/global-writing-rules.mdc
2. Client-Specific Guidelines - Read the active client's brand.mdc for voice and tone
3. Platform Rules - Apply appropriate platform-specific rules from -writing-rules/
4. Content Requirements - Follow the client's outputdoc.mdc specifications
5. Quality Check - Scan final content for AI detection patterns

Critical AI Rules

• Never cross-contaminate - Only reference files within the current client's folder
• Maintain voice consistency - Each client should sound distinctly different
• Follow naming conventions - Use the file naming pattern specified in outputdoc.mdc
• Apply universal standards - All content must pass AI detection prevention rules

Content Quality Standards

Universal Principles (Apply to All Clients)

• Lead with value, not ego
• Use active voice over passive voice
• Write conversationally, not academically
• Include specific examples and data points
• Hook readers within the first sentence
• End with clear next steps or calls-to-action

Platform-Specific Requirements

• LinkedIn: 3,000 character limit, first 200 characters critical for engagement
• Twitter: 280 character limit, engaging hooks, thread-friendly structure
• YouTube: Tutorial format with clear value proposition and implementation
• Email: Subject line + body, clear CTAs, personal tone
• Blog: SEO-optimized headlines, scannable structure, actionable insights

Getting Started as a Ghostwriter

Initial Setup

1. Study the system - Read this README completely
2. Review writing rules - Familiarize yourself with -writing-rules/ folder
3. Practice with examples - Create a test client folder to understand the workflow
4. Set up first client - Follow the client setup instructions above

Best Practices

• Batch similar work - Process all LinkedIn posts for a client before switching platforms
• Regular quality audits - Review content weekly for AI detection patterns
• Performance tracking - Note which content performs well for future iterations
• Client communication - Share content calendar and gather feedback regularly

Troubleshooting Common Issues

AI Detection Problems

• Content sounds too robotic → Review forbidden phrases in global writing rules
• Formulaic language → Vary sentence structure and use natural transitions
• Generic voice → Strengthen client-specific brand guidelines

Organization Issues

• Mixed client voices → Ensure strict folder separation and no cross-referencing
• Inconsistent naming → Standardize file naming conventions in each client's outputdoc.mdc
• Lost content → Use proper monthly subfolder organization

Quality Issues

• Low engagement → Analyze successful content patterns and iterate
• Off-brand content → Strengthen brand guidelines and voice examples
• Platform mismatches → Review platform-specific rules in -writing-rules/

System Requirements

This workspace works with:

• AI content generation tools (Claude, ChatGPT, etc.)
• Text editors that support Markdown (.mdc files)
• File organization systems (local folders or cloud storage)
• Content scheduling tools (Buffer, Hootsuite, etc.)
• Analytics platforms for performance tracking

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System Purpose: Enable professional ghostwriters to efficiently manage multiple clients with consistent quality, authentic voice, and scalable workflows.