Writer Skill

Generate content in your authentic voice across emails, blogs, social media, and reports.

Overview

The Writer skill learns from your writing samples and generates content that authentically sounds like you. Unlike generic AI content generation, this skill:

Maintains 6 distinct voice profiles (work email, personal email, blog, LinkedIn, Twitter, reports)
Interviews you like a Pulitzer-winning journalist to understand your message
Validates output against your authentic patterns
Saves versioned drafts to Obsidian

Key Innovation: Uses Claude's native LLM capabilities for voice analysis - no complex NLP libraries needed. Scripts just fetch samples, Geoffrey analyzes them.

Quick Start

1. Initial Setup (Before First Use)

Gather writing samples for voice profile creation:

cd ~/non-ic-code/geoffrey/skills/writer/scripts

# Extract email samples (3 accounts)
bun extract-email-samples.js --account psd --date-range "2024-06-01:2025-12-06" --max-samples 100 --output "/tmp/email-psd.json"
bun extract-email-samples.js --account kh --date-range "2024-06-01:2025-12-06" --max-samples 50 --output "/tmp/email-kh.json"
bun extract-email-samples.js --account hrg --date-range "2024-06-01:2025-12-06" --max-samples 50 --output "/tmp/email-hrg.json"

# Extract blog samples (requires Geoffrey Chrome)
cd ~/non-ic-code/geoffrey/skills/browser-control && ./scripts/launch-chrome.sh
cd ~/non-ic-code/geoffrey/skills/writer/scripts
bun extract-blog-samples.js --urls "https://psd401.ai/blog/post1,https://blog.krishagel.com/post2,..." --output "/tmp/blog-samples.json"

# Extract social samples (requires login to LinkedIn/X in Geoffrey Chrome)
bun extract-social-samples.js --platform linkedin --profile-url "https://linkedin.com/in/krishagel" --max-posts 50 --output "/tmp/social-linkedin.json"
bun extract-social-samples.js --platform twitter --profile-url "https://x.com/KrisHagel" --max-posts 50 --output "/tmp/social-twitter.json"

Then ask Geoffrey to analyze samples and create voice profiles:

Analyze my writing samples and create voice profiles.

Email: /tmp/email-psd.json, /tmp/email-kh.json, /tmp/email-hrg.json
Blog: /tmp/blog-samples.json
Social: /tmp/social-linkedin.json, /tmp/social-twitter.json

Estimated time: 30-45 minutes

2. Using the Skill

Once voice profiles are created:

write blog post about our AI implementation journey

write email to my team about next week's meeting

write LinkedIn post about Stanford AI Tinkery visit

Geoffrey will:

Load your voice profile
Interview you about the content
Create an outline for approval
Generate a draft in your voice
Validate against your patterns
Save to Obsidian

File Structure

skills/writer/
├── SKILL.md                            # Main skill definition with 6-phase workflow
├── scripts/
│   ├── extract-email-samples.js        # Fetch Gmail emails
│   ├── extract-blog-samples.js         # Fetch blog posts
│   ├── extract-social-samples.js       # Fetch LinkedIn/Twitter posts
│   └── README.md                       # Script documentation
├── templates/
│   ├── interview-questions.json        # Question sets per content type
│   └── voice-profile-template.json     # Empty profile structure
└── README.md                           # This file

Data Storage:

Voice profiles: ~/Library/Mobile Documents/com~apple~CloudDocs/Geoffrey/knowledge/writing-voice.json

Obsidian Drafts:

~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Personal_Notes/Geoffrey/Writing/
- Blog/
- Email/
- Social/
- Reports/

Voice Profiles

Six distinct profiles capture different writing contexts:

Profile	Source	Target Samples	Confidence
`email_work`	PSD Gmail (sent, 6mo)	50+ emails	Check writing-voice.json
`email_personal`	Personal/HRG Gmail	50+ emails	Check writing-voice.json
`blog_technical`	psd401.ai + blog.krishagel.com	10+ posts	Check writing-voice.json
`social_linkedin`	LinkedIn posts	30+ posts	Check writing-voice.json
`social_twitter`	X/Twitter posts	30+ posts	Check writing-voice.json
`report_formal`	User-provided samples	5-10 reports	Check writing-voice.json

Confidence Levels:

High (0.85+): 50+ samples - voice well established
Moderate (0.70-0.84): 20-49 samples - patterns emerging
Low (<0.70): <20 samples - insufficient, warn user

6-Phase Workflow

Voice Profile Selection & Validation
- Detect content type
- Load profile from writing-voice.json
- Check confidence, warn if low
Deep Interview (Adaptive)
- 3-5 questions for tweets/social
- 4-8 questions for emails
- 8-12 questions for blogs
- 15+ questions for reports
Content Planning & Outline
- Create structure based on interview + content type
- Apply voice preferences
- User approves outline
Draft Generation
- Load identity from identity-core.json
- Apply voice characteristics (tone, structure, vocabulary)
- Write naturally with voice context
Validation & Refinement
- Geoffrey self-validates against voice profile
- Score 0-100 on tone, structure, vocab, formatting
- Refine if score <85
Storage & Versioning
- Save to Obsidian with frontmatter
- Return text for copy/paste
- Offer to open in Obsidian

Integration Points

knowledge-manager: Load identity context for personality alignment
google-workspace: Fetch email samples from Gmail
browser-control: Scrape blog/social posts
obsidian-manager: Save versioned drafts

Example Usage

Quick Work Email

You: write email to my team about next week's leadership meeting

Geoffrey:
- Uses email_work profile (confidence: 0.92)
- Quick interview (4 questions)
- Generates ~200 word email
- Direct, bullet-point style
- Validation score: 89/100

Blog Post

You: write blog about our AI implementation journey

Geoffrey:
- Uses blog_technical profile (confidence: 0.78)
- Standard interview (11 questions)
- Generates ~850 word post
- Accessible tone, staff quotes, chronological
- Validation score: 87/100
- Saves to Geoffrey/Writing/Blog/2025-12-06-ai-implementation.md

LinkedIn Post

You: LinkedIn post about Stanford AI Tinkery visit

Geoffrey:
- Uses social_linkedin profile (confidence: 0.91)
- Quick interview (5 questions)
- Generates ~180 word post
- Thought leadership tone
- Validation score: 92/100

Maintenance

Quarterly Voice Refresh

Voice profiles should be refreshed every 3 months as writing styles evolve:

# Re-extract recent samples
bun scripts/extract-email-samples.js --account psd --date-range "2025-09-01:2025-12-06" --output "/tmp/email-refresh.json"

# Ask Geoffrey to update profile
"Update my email_work profile with /tmp/email-refresh.json"

Geoffrey will auto-warn if profiles are >12 months old.

Troubleshooting

See scripts/README.md for detailed troubleshooting.

Common issues:

"No voice profile found": Run initial setup to create profiles
"Low confidence warning": Gather more samples (target 50+ for emails, 10+ for blogs)
"Geoffrey Chrome not running": cd ~/non-ic-code/geoffrey/skills/browser-control && ./scripts/launch-chrome.sh
"Failed to extract social posts": Log into LinkedIn/X in Geoffrey Chrome first

Development

Architecture:

Scripts fetch raw writing samples (email, blog, social)
Geoffrey analyzes samples natively using LLM capabilities
No NLP libraries - cleaner, more maintainable
Voice profiles store samples + Geoffrey's analysis

Adding New Content Types:

Create extraction script if needed
Add profile to voice-profile-template.json
Add interview questions to interview-questions.json
Update SKILL.md workflow
Extract samples and ask Geoffrey to analyze

Future Enhancements

Real-time learning (auto-analyze new emails monthly)
A/B testing (generate 2 versions, learn from choices)
Collaborative voice (blend user + co-author)
Multi-language (Spanish voice profiles)
Performance tracking (voice drift detection)
Audience-aware sub-profiles

Version

v0.1.0 - Initial implementation

6 voice profiles
Sample extraction scripts
6-phase workflow with checkpoints
Native LLM validation
Obsidian integration